Mobile intelligent road infrastructure system

ABSTRACT

Provided herein is technology relating to automated driving and particularly, but not exclusively, to a mobile intelligent road infrastructure technology configured to serve automated driving systems by providing, supplementing, and/or enhancing autonomous driving functions for connected automated vehicles under common and unusual driving scenarios.

STATEMENT OF RELATED APPLICATIONS

This application claims priority to U.S. Provisional Patent ApplicationNo. 63/155,545, filed Mar. 2, 2021, the entire contents of which areincorporated herein by reference for all purposes.

FIELD

Provided herein is technology relating to automated driving andparticularly, but not exclusively, to a mobile intelligent roadinfrastructure technology configured to serve automated driving systemsby providing, supplementing, and/or enhancing autonomous drivingfunctions for connected automated vehicles under common and unusualdriving scenarios.

BACKGROUND

With the development of new-generation information technologies such asartificial intelligence, cloud computing, and the Internet of Things,the development of transportation infrastructure is facing newopportunities and new challenges. For example, a connected and automatedvehicle highway system (CAVH) provides important technologies foralleviating traffic congestion, improving traffic safety, and reducingtraffic pollution. See, e.g., U.S. Pat. No. 10,380,886 and U.S. Pat.App. Pub. No. 2019/0340921, each of which is incorporated herein byreference.

An intelligent roadside system provides collaborative sensing,collaborative prediction, collaborative decision-making, andcollaborative vehicle control for CAVH systems. While existingintelligent roadside systems typically comprise fixed, immobileinfrastructure components (see, e.g., U.S. Pat. No. 10,692,365 and U.S.Pat. App. Pub. No. 2020/0168081, each of which is incorporated herein byreference), automated driving systems (e.g., CAVH systems) would benefitfrom mobile intelligent roadside infrastructure technologies.

SUMMARY

Accordingly, provided herein is a mobile intelligent roadsideinfrastructure technology. In particular, the technology provides aMobile Intelligent Road Infrastructure System (MIRIS) and relatedmethods (e.g., management methods) that serve automated driving systems(ADS), such as a connected and automated vehicle highway (CAVH) system.The MIRIS and related methods provide, supplement, enhance, exceed,improve, and/or replace macroscopic, mesoscopic, and/or microscopicautomated driving functions (e.g., sensing, prediction, decision-making,and/or control) for connected automated vehicles (CAV) at any vehicleintelligence level. In some embodiments, the MIRIS improves an ADS byproviding dynamic characteristics, flexibility, and increasedcapabilities to an ADS. For example, an ADS (e.g., a CAVH system)improved by the MIRIS is configured to adjust and/or deploy mobileroadside infrastructure (e.g., components and/or equipment) flexibly andquickly to provide automated driving functions. Embodiments of the MIRIStechnology provided herein enhance ADS (e.g., CAVH systems) andcomponents of ADS systems (e.g., CAVH system components) by providingmobile infrastructure and systems and methods for managing mobileinfrastructure. The MIRIS also improves an ADS by assisting the ADS tomanage emergency scenarios and long-tail scenarios of automated driving.

As described herein, embodiments of the MIRIS comprise: (1) a MobileRoadside Intelligent Unit (MRIU); (2) a Traffic Operation Center (TOC);(3) a Traffic Control Center (TCC) and Traffic Control Unit (TCU);and/or (4) a roadside communication system. Further, in someembodiments, the MIRIS (e.g., a TOC of the MIRIS) comprises a RoadsideUnit Management Control (RUMC) system that determines locations for MRIUand/or adjusts the location of MRIU. For example, in some embodiments,the RUMC system adjusts the location of MRIU to provide the MIRIS withfunctions to enhance the service capabilities of ADS (e.g., CAVHsystem), replace a faulty roadside intelligent unit (RIU), and/or assistsite selection for an RIU. Consequently, the MIRIS improves thereliability, mobility, and/or serviceability of an ADS (e.g., a CAVHsystem).

Accordingly, the MIRIS technology supplements and complements previousADS (e.g., CAVH systems) comprising fixed infrastructure. For example,the MIRIS technology provides an ADS (e.g., CAVH system) with dynamicand flexible infrastructure, functions, and/or capabilities to controlvehicles and manage traffic in a broader range of scenarios, e.g.,long-tail environments and scenarios. As described herein, mobileroadside intelligent units are organized and controlled by the MIRIS(e.g., by a TOC) to enhance the practicability, flexibility, andreliability of ADS (e.g., CAVH systems). The technology provided hereinthus provides ADS (e.g., CAVH systems) with functions and/orcapabilities to control vehicles and manage traffic in a variety ofcomplex scenarios and to improve the safety and reliability ofautonomous driving. Moreover, in some embodiments, the MIRIS improvesthe efficiency of infrastructure deployment and increases theeffectiveness and implementation of automated driving systems (e.g., aCAVH system).

Accordingly, provided herein is technology related to a MobileIntelligent Road Infrastructure System (MIRIS). In some embodiments, theMIRIS comprises one or more of the following subcomponents: a MobileRoadside Intelligent Unit (MRIU); Traffic Operation Center (TOC);Traffic Control Center (TCC) and Traffic Control Unit (TCU); and/or aroadside communication system. In some embodiments, one or more of thesubcomponents is a physical subsystem. Accordingly, in some embodiments,the MIRIS comprises one or more of the following physical subsystems: aMobile Roadside Intelligent Unit (MRIU); Traffic Operation Center (TOC);Traffic Control Center (TCC) and Traffic Control Unit (TCU); and/or aroadside communication system. In some embodiments, the MIRIS isconfigured to support an automated driving system (ADS). In someembodiments, the MIRIS is configured to support a connected andautomated vehicle highway (CAVH) system. In some embodiments, the MIRISis configured to support an ADS by providing one or more mobile roadsideintelligent units (MRIU) to said ADS.

In some embodiments, the MIRIS is supported by a multi-level cloudplatform, a high-precision map system, an energy supply system, and/oran information security system. In some embodiments, an ADS and/or aCAVH system comprises said multi-level cloud platform, saidhigh-precision map system, said energy supply system, and/or saidinformation security system. In some embodiments, the ADS is aroad-based ADS, a connected and automated vehicle (CAV)-based ADS, acloud-based ADS, and/or a high precision map-based ADS.

In some embodiments, the MIRIS is configured to serve automated vehicles(AV) and/or connected and automated vehicles (CAV) having anintelligence level of V1, V1.5, V2, V3, V4, and/or V5. In someembodiments, the MIRIS is configured to receive data from a VehicleIntelligent Unit (VIU) and/or an MRIU, generate vehicle controlinstructions, and/or send vehicle control instructions to a VIU. In someembodiments, the MIRIS is configured to complement, enhance, back-up,elevate, and/or replace automated driving functions provided by an ADSand/or CAVH system.

In some embodiments, the MIRIS “complements” the automated drivingfunctions of an ADS (e.g., CAVH system), IRIS, and/or a vehicle byproviding sensing and perception, decision-making, and/or vehiclecontrol functions for an ADS (e.g., CAVH system), IRIS, and/or a vehiclethat is not able to perform one or more of sensing and perception,decision-making, and/or vehicle control functions. Accordingly, in someembodiments, the MIRIS “completes” the suite of automated drivingfunctions by providing the automated driving functions that are notprovided by the vehicle or that are not adequately provided by the ADS(e.g., CAVH system), IRIS, and/or a vehicle.

In some embodiments, the MIRIS “enhances” the automated drivingfunctions of an ADS (e.g., CAVH system), IRIS, and/or a vehicle byimproving the vehicle driving functions provided by the ADS (e.g., CAVHsystem), IRIS, and/or a vehicle. For example, in some embodiments, theMIRIS enhances automated driving functions of an ADS (e.g., CAVHsystem), IRIS, and/or a vehicle by improving sensing and perception,decision-making, and/or vehicle control functions for an ADS (e.g., CAVHsystem), IRIS, and/or a vehicle that is not adequately performingsensing and perception, decision-making, and/or vehicle controlfunctions.

In some embodiments, the MIRIS “backs-up” the automated drivingfunctions of an ADS (e.g., CAVH system), IRIS, and/or a vehicle byproviding system redundancies configured to provide sensing andperception, decision-making, and/or vehicle control functions to avehicle when an ADS (e.g., CAVH system), IRIS, and/or a vehicleexperiences a failure that decreases the sensing and perception,decision-making, and/or vehicle control functions of the an ADS (e.g.,CAVH system), IRIS, and/or a vehicle.

In some embodiments, the MIRIS “elevates” a vehicle intelligence levelfrom a lower vehicle intelligence level to a higher vehicle intelligencelevel. In some embodiments, the MIRIS elevates a vehicle automationlevel from a lower vehicle automation level to a higher vehicleautomation level, where the vehicle automation level is as describedherein and/or as defined by SAE International Standard J3016, “Taxonomyand Definitions for Terms Related to Driving Automation Systems forOn-Road Motor Vehicles” (published in 2014 (J3016_201401) and as revisedin 2016 (J3016_201609) and 2018 (J3016_201806), each of which isincorporated herein by reference.

In some embodiments, the MIRIS “replaces” the automated drivingfunctions of an ADS (e.g., CAVH system), IRIS, and/or a vehicle by fullyand/or partially replacing the vehicle driving functions provided by anADS (e.g., CAVH system), IRIS, and/or a vehicle with vehicle drivingfunctions provided by the MIRIS. For example, in some embodiments, theMIRIS fully and/or partially replaces one or more automated drivingfunctions of an ADS (e.g., CAVH system), IRIS, and/or a vehicle by fullyand/or partially replacing sensing and perception, decision-making,and/or vehicle control functions for an ADS (e.g., CAVH system), IRIS,and/or a vehicle that is not performing sensing and perception,decision-making, and/or vehicle control functions and/or for an ADS(e.g., CAVH system), IRIS, and/or a vehicle that is not adequatelyand/or not fully performing sensing and perception, decision-making,and/or vehicle control functions. In some embodiments, the MIRIS“replaces” the automated driving functions of an ADS (e.g., CAVHsystem), IRIS, and/or a vehicle by fully and/or partially replacing thevehicle driving functions provided by an ADS (e.g., CAVH system), IRIS,and/or a vehicle with vehicle driving functions provided by the MIRISduring an emergency situation and/or in a long-tail scenario.

In some embodiments, the MIRIS is configured to provide sensing,prediction, decision-making, and/or vehicle control functions forautomated driving. In some embodiments, the automated driving functionsare sensing, prediction, decision-making, and/or vehicle controlfunctions.

In some embodiments, the MIRIS is configured to perform MRIU managementand control methods comprising supporting IRIS by deploying an MRIU tosaid IRIS. In some embodiments, the MRIU provides sensing, prediction,decision-making, and/or vehicle control functions to IRIS. In someembodiments, the MRIU performs the management and control methods whenan RIU malfunctions, an RIU is failing, an RIU is unable to adequatelyprovide and/or support automated driving functions, and/or when IRIS hasno RIU deployed at a location where automated driving services areneeded.

In some embodiments, the MIRIS further comprises a Roadside UnitManagement Control (RUMC) system. In some embodiments, the RUMC systemis configured to perform methods comprising optimizing RIU deploymentlocations. In some embodiments, the RUMC system is further configured toperform methods comprising deploying an MRIU. In some embodiments, theMRIU is configured to collect IRIS and/or RIU performance data. In someembodiments, the performance data describes sensing and detectionfunctions of said IRIS and/or said RIU. In some embodiments, the RUMCsystem is configured to perform methods comprising identifying optimaldeployment locations. In some embodiments, the RUMC system is configuredto perform methods comprising deploying an MRIU to an optimal deploymentlocation. In some embodiments, the RUMC is configured to perform methodscomprising deploying a number of MRIU to IRIS; collecting IRISperformance data describing sensing and detection functions of IRIS;and/or identifying optimal locations for RIU based on said IRISperformance data. In some embodiments, the RUMC system is configured toperform methods comprising communicating said optimal locations for RIUto IRIS; and/or deploying MRIU to IRIS. In some embodiments, the MRIUare deployed at said optimal locations.

In some embodiments, the TOC is configured to predict traffic state,manage traffic, plan traffic, and/or make decisions. In someembodiments, the TOC is configured to predict traffic state on amesoscopic and/or macroscopic time scale. In some embodiments, the TOCis configured to interact with and/or receive support from a multi-levelcloud platform. In some embodiments, the TOC is configured to providevehicle control and traffic management strategies, adjust a position ofan MRIU, and/or provide automated driving functions. In someembodiments, the TOC is configured to provide functions through a RUMCsystem of MIRIS. In some embodiments, the TOC is configured to receivedata describing real-time traffic status and/or real-time demand for ADSservices; and/or provide automated driving functions based on said data.In some embodiments, the TOC is configured to determine real-timetraffic status and/or real-time demand for ADS services; and/or provideautomated driving functions based on said real-time traffic statusand/or demand for ADS services. In some embodiments, the TOC isconfigured to provide automated driving functions for a number ofdifferent automated driving scenarios.

In some embodiments, the MRIU is/are configured to exchange data and/orinformation with RIU, TCU, TCC, TOC, and/or VIU.

In some embodiments, the roadside communication system is configured toprovide wired and/or wireless communications between MIRISsubcomponents. In some embodiments, the roadside communication system isconfigured to provide wired and/or wireless communications for exchangeof data and/or information. In some embodiments, the roadsidecommunication system is configured to provide wired and/or wirelesscommunications using LTE-V2X, 4G, 5G, 6G, and/or 7G cellular.

In some embodiments, the multi-level cloud platform comprises and/orprovides a macroscopic cloud, a mesoscopic cloud, and/or a microscopiccloud. In some embodiments, the multi-level cloud platform comprises amacroscopic cloud configured to provide (and/or to provide support for)computing and/or data storage functions for TOC; a mesoscopic cloudconfigured to provide (and/or to provide support for) computing and/ordata storage functions for TCC; and/or a microscopic cloud configured toprovide (and/or to provide support for) computing and/or data storagefunctions for TCU. Additional discussion of the multi-level cloudplatform and the macroscopic cloud, a mesoscopic cloud, and/ormicroscopic cloud is provided by, e.g., U.S. Pat. App. Ser. No.63/149,804, incorporated herein by reference.

In some embodiments, the high-precision map system is configured toprovide positioning and mapping services for the MRIU and/or for a RUMCsystem.

In some embodiments, the energy supply system is configured to providepower for the operations of MIRIS and/or for the component subsystems ofthe MIRIS.

In some embodiments, the information security system is configured tomaximize communication security and/or information storage security ofthe MIRIS and/or for the component subsystems of the MIRIS.

In some embodiments, the RUMC system comprises an informationtransmission subsystem, a data management subsystem, a mobile servicesubsystem, and/or a security control subsystem. In some embodiments, theinformation transmission subsystem is configured to exchange data and/orinformation with the RUMC system, MRIU, and/or IRIS. In someembodiments, the data management subsystem is configured to record,store, and/or back-up data and/or information from MRIU. In someembodiments, the data and/or information from MRIU comprises MRIUposition, MRIU state, MRIU energy consumption, scene environmentinformation, real-time sensing data, and/or historical MRIU movementplans. In some embodiments, the mobile service subsystem is configuredto analyze a scene and/or parameters recorded in the data managementsubsystem; formulate a MRIU deployment plan; and/or generate MRIUcontrol strategies for adjusting a location of an MRIU. In someembodiments, the mobile service subsystem is further configured toprovide a mobile command comprising control instructions for adjustingthe position of a MRIU. In some embodiments, the mobile command isprovided to said security control subsystem. In some embodiments, thesecurity control subsystem is configured to confirm a mobile commandprovided by the mobile service subsystem; and send the mobile command tothe information transmission subsystem for execution of said mobilecommand. In some embodiments, execution of said mobile command comprisesperforming a method comprising adjusting a position of a MRIU.

In some embodiments, the RUMC system is configured to perform a methodcomprising receiving, e.g., by the information transmission subsystem, aservice request sent by the IRIS or the MRIU; optionally backing up,e.g., by the data management subsystem, the service request; analyzing,e.g., by the mobile service subsystem, the specific working scenario ofthe service request; determining, e.g., by the mobile service subsystem,if the MIRIS can provide services in the specific working scenario;and/or performing either (i) or (ii): (i) if the MIRIS cannot provideservices in the specific working scenario: methods comprise generating,e.g., by the mobile service subsystem, a command that the MIRIS cannotmeet the service requirements; transmitting the command to theinformation transmission subsystem; and sending, e.g., by theinformation transmission subsystem, the command to IRIS and/or MRIUindicating that MIRIS cannot meet the service requirements; or (ii) ifthe MIRIS can provide services in the specific working scenario: methodscomprise selecting, e.g., by the mobile service subsystem, work modulesaccording to the specific service requirements; generating a layoutscheme and MRIU control instructions; confirming, e.g., by the safetycontrol subsystem, the layout scheme and MRIU control instructions; andsending, e.g., by the information transmission subsystem, the layoutscheme and MRIU control instructions to IRIS and/or MRIU.

In some embodiments, the mobile service subsystem comprises a dynamicdeployment module, an emergency service module, and/or an auxiliaryapplication module. In some embodiments, the dynamic deployment moduleis configured to perform a method comprising adjusting the location ofMRIU to balance the ADS services and demands for ADS services. In someembodiments, the dynamic deployment module is configured to adjust thelocation of MRIU to balance the ADS services and demands for ADSservices. In some embodiments, the dynamic deployment module isconfigured to adjust the location of MRIU to rebalance the ADS servicesand demands for ADS services after a change in traffic flow over timeand/or in different geographic areas. In some embodiments, the emergencyservice module is configured to provide and/or support automated drivingin long tail scenarios; generate MRIU management and/or controlstrategies in response to emergency scenarios; and/or supplement and/orenhance ADS sensing, prediction, decision-making, and/or vehicle controlfunctions for long-tail and/or emergency scenarios. In some embodiments,auxiliary application module is configured to generate MRIU controlstrategies or schemes for other service requirements of the ADS.

In some embodiments, the MRIU comprises an intelligent sensing module;an intelligent communication module; an intelligent computing module; anintelligent decision control module; an intelligent mobile module;and/or an intelligent display module.

In some embodiments, the intelligent sensing module is configured toprovide environment sensing to sense the environment and/or to providemobile state sensing to sense the mobile state of an MRIU. In someembodiments, the environment sensing provides data describing theenvironment as an input for an ADS and/or CAVH system. In someembodiments, the mobile state sensing comprises use of a GNSS to sensethe dynamic parameters of an MRIU, an inertial navigation system tosense the dynamic parameters of an MRIU, and/or other systems configuredto sense the dynamic parameters of an MRIU. In some embodiments, thedynamic parameters of an MRIU provide information support for themovement of the MRIU. In some embodiments, the intelligent communicationmodule is configured to provide and/or support multi-mode communication.In some embodiments, the multi-mode communication comprises use ofLTE-V2X, WiFi, GPS/BeiDou, 5G, 6G, and/or 7G cellular communications. Insome embodiments, the intelligent communication module is configured toprovide and/or support low-delay, high-reliability, and/or high-densitydata exchange between MRIU and RIU, TCU, TCC, TOC, and/or VIU.

In some embodiments, the intelligent computing module is configured toprovide data fusion, data storage, and/or data feature extraction forsensing data and/or multi-source sensing data; predict the traffic flowstate; and/or and optimize the moving speed and/or moving path for anMRIU. In some embodiments, the intelligent computing module isconfigured to predict the traffic flow state on a microscopic timescale. In some embodiments, the intelligent computing module isconfigured to optimize the moving speed and/or moving path for an MRIUin real-time. In some embodiments, the intelligent computing module isconfigured to be supported by a component configured to provide edgecomputing technology. In some embodiments, the intelligent computingmodule is configured to formulate control strategies, generate vehiclecontrol instructions, and/or distribute vehicle control informationand/or instructions for CAV. In some embodiments, the CAV have anintelligence level of V1, V1.5, V2, V3, V4, or V5. In some embodiments,the intelligent computing module is configured to formulate controlstrategies, generate vehicle control instructions, and/or distributevehicle control information and/or instructions for CAV using dataprocessed by the intelligent computing module.

In some embodiments, the intelligent decision control module isconfigured to determine the moving speed and/or the moving path of anMRIU.

In some embodiments, the intelligent mobile module is configured to movean MRIU. In some embodiments, the intelligent mobile module isconfigured to move an MRIU according to a moving speed and/or a movingpath determined and/or provided by the intelligent decision controlmodule. In some embodiments, the intelligent mobile module is configuredto monitor the movement status and/or energy consumption of a MRIU. Insome embodiments, the intelligent mobile module is configured to monitorthe movement status and/or energy consumption of a MRIU in real-time.

In some embodiments, the intelligent display module is configured toassist CAV. In some embodiments, the intelligent display module isconfigured to assist CAV at an intelligence level of V1, V1.5, V2, V3,V4, or V5. In some embodiments, the intelligent display module isconfigured to assist CAV having a VIU malfunction and/or VIU failure.

In some embodiments, the intelligent computing module comprises a datastorage unit, an edge computing unit, and/or a route planning unit. Insome embodiments, the data storage unit is configured to store trafficinformation collected by the intelligent sensing module; back up taskinstructions; and/or record the operating parameters of the MRIU. Insome embodiments, the traffic information is processed by themulti-level cloud platform. In some embodiments, the task instructionsare sent by the RUMC. In some embodiments, the operating parameters ofthe MRIU comprise time, MRIU location, MRIU speed, and/or MRIU energyconsumption.

In some embodiments, the edge computing unit is configured to conductdata fusion and/or data feature extraction for traffic information. Insome embodiments, the traffic information is collected by theintelligent sensing module. In some embodiments, the edge computing unitis configured to combine mesoscopic traffic information and macroscopictraffic information. In some embodiments, the mesoscopic trafficinformation and/or macroscopic traffic information is provided by themulti-level cloud platform. In some embodiments, the edge computing unitis configured to predict lane traffic flow parameters and/or themovement state of CAV. In some embodiments, the lane traffic flowparameters and/or the movement state of CAV are on a microscopic and/ormesoscopic time scale. In some embodiments, the edge computing unit isconfigured to supplement the computing capacity of the ADS. In someembodiments, the edge computing unit is configured to identify, analyze,and/or predict a change of the external environment and/or a movingstate of an MRIU.

In some embodiments, the route planning unit is configured to plan amoving path and/or a trajectory of MRIU. In some embodiments, the routeplanning unit is configured to optimize a moving speed of an MRIUaccording to information provided by the data storage unit and/or by theedge computing unit.

In some embodiments, the intelligent decision control module comprises acontrol unit, a decision-making unit, and/or a route selection unit. Insome embodiments, the control unit is configured to generate controlinstructions for CAV. In some embodiments, the control unit isconfigured to generate control instructions for CAV having anintelligence level of V1, V1.5, V2, V3, V4, or V5. In some embodiments,the control unit is configured to maximize the safety control of CAV inspecial scenarios according to the information provided by thedecision-making unit. In some embodiments, the decision-making unit isconfigured to provide and/or improve a decision-making function of CAV.In some embodiments, the decision-making unit is configured to provideand/or improve a decision-making function of CAV having an intelligencelevel of V1, V1.5, V2, V3, V4, or V5. In some embodiments, thedecision-making unit is configured to provide and/or improve adecision-making function of CAV in a range of scenarios and/or toprovide traffic management decisions for a range of scenarios. In someembodiments, the route selection unit is configured to determine a pathfor a MRIU. In some embodiments, the route selection unit is configuredto determine a path for a MRIU according to a deployment task providedby the RUMC and/or according to a MRIU deployment scheme provided by theroute planning unit. In some embodiments, the route selection unit isconfigured to determine if a planned path for a MRIU meets a servicetask assigned by the RUMC.

In some embodiments, the MRIU is configured to perform a methodcomprising receiving, e.g., by the intelligent communication module, adeployment command from the RUMC; planning, e.g., by the intelligentcomputing module, a moving path and/or a moving speed for MRIU;selecting, e.g., by the intelligent decision control module, a movingpath and/or moving speed and sending the moving path and/or moving speedinformation to the intelligent mobile module; moving, e.g., by theintelligent mobile module, the MRIU according to the moving path and/ormoving speed; and monitoring, e.g., by the intelligent mobile module,the movement status of the MRIU. In some embodiments, planning a movingpath and/or a moving speed for MRIU comprises using and/or combiningprediction information and/or attribute information of the MRIU. In someembodiments, the method comprises detecting, e.g., by the intelligentsensing module, obstacles in the moving path and/or abnormal conditions;and adjusting, e.g., by the intelligent computing module adjusts, theMRIU moving path based on real-time environment information and/or theoperating parameters of the MRIU to provide a new path. In someembodiments, the method comprises determining, e.g., by the intelligentdecision control module, if the MRIU can reach the target position ontime according to the new path. In some embodiments, the methodcomprises determining, e.g., by the decision control module, that theMRIU cannot reach the task location on time according to the new path;and uploading task failure information to the RUMC. In some embodiments,the method further comprises waiting, e.g., by the MRIU, for furtherinstructions from the RUMC. In some embodiments, the method comprisesdetermining, e.g., by the decision control module, that the MRIU canreach the task location on time according to the new path; and moving,e.g., by the intelligent mobile module, the MRIU through the new path.In some embodiments, the method comprises confirming, e.g., by theintelligent decision control module, the moving path and/or movingspeed. In some embodiments, monitoring the movement status of the MRIUis monitoring the movement status of the MRIU in real-time.

In some embodiments, the technology provides a mobile roadsideintelligent unit (MRIU). In some embodiments, the MRIU comprises anintelligent sensing module; an intelligent communication module; anintelligent computing module; an intelligent decision control module; anintelligent mobile module; and/or an intelligent display module. In someembodiments, intelligent sensing module is configured to provideenvironment sensing to sense the environment and/or to provide mobilestate sensing to sense the mobile state of an MRIU. In some embodiments,the environment sensing provides data describing the environment as aninput for an ADS and/or CAVH system. In some embodiments, the mobilestate sensing comprises use of a GNSS to sense the dynamic parameters ofan MRIU, an inertial navigation system to sense the dynamic parametersof an MRIU, and/or other systems configured to sense the dynamicparameters of an MRIU. In some embodiments, the dynamic parameters of anMRIU provide information support for the movement of the MRIU. In someembodiments, the intelligent communication module is configured toprovide and/or support multi-mode communication. In some embodiments,the multi-mode communication comprises use of LTE-V2X, WiFi, GPS/BeiDou,5G, 6G, and/or 7G. In some embodiments, the intelligent communicationmodule is configured to provide and/or support low-delay,high-reliability, and/or high-density data exchange between MRIU andRIU, TCU, TCC, TOC, and/or VIU. In some embodiments, the intelligentcomputing module is configured to provide data fusion, data storage,and/or data feature extraction for sensing data and/or multi-sourcesensing data; predict the traffic flow state; and/or and optimize themoving speed and/or moving path for an MRIU. In some embodiments, thecomputing module is configured to predict the traffic flow state on amicroscopic time scale. In some embodiments, the intelligent computingmodule is configured to optimize the moving speed and/or moving path foran MRIU in real-time. In some embodiments, the intelligent computingmodule is configured to be supported by a component configured toprovide edge computing technology. In some embodiments, the intelligentcomputing module is configured to formulate control strategies, generatevehicle control instructions, and/or distribute vehicle controlinformation and/or instructions for CAV. In some embodiments, the CAVhave an intelligence level of V1, V1.5, V2, V3, V4, or V5. In someembodiments, the intelligent computing module is configured to formulatecontrol strategies, generate vehicle control instructions, and/ordistribute vehicle control information and/or instructions for CAV usingdata processed by the intelligent computing module. In some embodiments,the intelligent decision control module is configured to determine themoving speed and/or the moving path of an MRIU. In some embodiments, theintelligent mobile module is configured to move an MRIU. In someembodiments, the intelligent mobile module is configured to move an MRIUaccording to a moving speed and/or a moving path determined and/orprovided by the intelligent decision control module. In someembodiments, the intelligent mobile module is configured to monitor themovement status and/or energy consumption of a MRIU. In someembodiments, the intelligent mobile module is configured to monitor themovement status and/or energy consumption of a MRIU in real-time. Insome embodiments, the intelligent display module is configured to assistCAV. In some embodiments, the intelligent display module is configuredto assist CAV at an intelligence level of V1, V1.5, V2, V3, V4, or V5.In some embodiments, the intelligent display module is configured toassist CAV having a VIU malfunction and/or VIU failure. In someembodiments, the intelligent computing module comprises a data storageunit, an edge computing unit, and/or a route planning unit. In someembodiments, the data storage unit is configured to store trafficinformation collected by the intelligent sensing module; back up taskinstructions; and/or record the operating parameters of the MRIU. Insome embodiments, the traffic information is processed by themulti-level cloud platform. In some embodiments, the task instructionsare sent by the RUMC. In some embodiments, the operating parameters ofthe MRIU comprise time, MRIU location, MRIU speed, and/or MRIU energyconsumption. In some embodiments, the edge computing unit is configuredto conduct data fusion and/or data feature extraction for trafficinformation. In some embodiments, the traffic information is collectedby the intelligent sensing module. In some embodiments, the edgecomputing unit is configured to combine mesoscopic traffic informationand macroscopic traffic information. In some embodiments, the mesoscopictraffic information and/or macroscopic traffic information is providedby the multi-level cloud platform. In some embodiments, the edgecomputing unit is configured to predict lane traffic flow parametersand/or the movement state of CAV. In some embodiments, the lane trafficflow parameters and/or the movement state of CAV are on a microscopicand/or mesoscopic time scale. In some embodiments, the edge computingunit is configured to supplement the computing capacity of the ADS. Insome embodiments, the edge computing unit is configured to identify,analyze, and/or predict a change of the external environment and/or amoving state of an MRIU. In some embodiments, the route planning unit isconfigured to plan a moving path and/or a trajectory of MRIU. In someembodiments, the route planning unit is configured to optimize a movingspeed of an MRIU according to information provided by the data storageunit and/or by the edge computing unit. In some embodiments, theintelligent decision control module comprises a control unit, adecision-making unit, and/or a route selection unit. In someembodiments, the control unit is configured to generate controlinstructions for CAV. In some embodiments, the control unit isconfigured to generate vehicle control instructions for CAV having anintelligence level of V1, V1.5, V2, V3, V4, or V5. In some embodiments,the control unit is configured to maximize the safety control of CAV inspecial scenarios according to the information provided by thedecision-making unit. In some embodiments, the decision-making unit isconfigured to provide and/or improve a decision-making function of CAV.In some embodiments, the decision-making unit is configured to provideand/or improve a decision-making function of CAV having an intelligencelevel of V1, V1.5, V2, V3, V4, or V5. In some embodiments, thedecision-making unit is configured to provide and/or improve adecision-making function of CAV in a range of scenarios and/or toprovide traffic management decisions for a range of scenarios. In someembodiments, the route selection unit is configured to determine a pathfor a MRIU. In some embodiments, the route selection unit is configuredto determine a path for a MRIU according to a deployment task providedby the RUMC and/or according to a MRIU deployment scheme provided by theroute planning unit. In some embodiments, the route selection unit isconfigured to determine if a planned path for a MRIU meets a servicetask assigned by the RUMC.

Also provided herein are methods employing any of the systems describedherein for the management of one or more aspects of automated driving ofa CAV and/or for the management of one or more aspects of trafficcontrol. The methods include those processes undertaken by individualparticipants in the system (e.g., drivers, public or private local,regional, or national transportation facilitators, government agencies,etc.) as well as collective activities of one or more participantsworking in coordination or independently from each other.

Some portions of this description describe the embodiments of thetechnology in terms of algorithms and symbolic representations ofoperations on information. These algorithmic descriptions andrepresentations are commonly used by those skilled in the dataprocessing arts to convey the substance of their work effectively toothers skilled in the art. These operations, while describedfunctionally, computationally, or logically, are understood to beimplemented by computer programs or equivalent electrical circuits,microcode, or the like. Furthermore, it has also proven convenient attimes to refer to these arrangements of operations as modules, withoutloss of generality. The described operations and their associatedmodules may be embodied in software, firmware, hardware, or anycombinations thereof.

Certain steps, operations, or processes described herein may beperformed or implemented with one or more hardware or software modules,alone or in combination with other devices. In some embodiments, asoftware module is implemented with a computer program productcomprising a computer-readable medium containing computer program code,which can be executed by a computer processor for performing any or allsteps, operations, or processes described.

In some embodiments, the technology provides a method of controllingvehicles and/or managing traffic comprising providing a MIRIS asdescribed herein. In some embodiments, the technology provides a methodof controlling vehicles and/or managing traffic comprising providing aMRIU as described herein. In some embodiments, the technology provides amethod of supporting an ADS (e.g., a CAVH system) comprising providing aMIRIS as described herein and/or a MRIU as described herein.

For example, in some embodiments, methods comprise providing a MobileIntelligent Roadside Infrastructure System (MIRIS) comprising a MobileRoadside Intelligent Unit (MRIU); receiving, by an informationtransmission subsystem, a service request sent by an IRIS or a MRIU;analyzing, by a mobile service subsystem, the specific working scenarioof the service request; determining, e.g., by the mobile servicesubsystem, if the MIRIS can provide services in the specific workingscenario; and/or performing either (i) or (ii): i) if the MIRIS cannotprovide services in the specific working scenario: generating, e.g., bythe mobile service subsystem, a command that the MIRIS cannot meet theservice requirements; transmitting the command to the informationtransmission subsystem; and sending, e.g., by the informationtransmission subsystem, the command to IRIS and/or MRIU indicating thatMIRIS cannot meet the service requirements; or (ii) if the MIRIS canprovide services in the specific working scenario: selecting, e.g., bythe mobile service subsystem, work modules according to the specificservice requirements; generating a layout scheme and MRIU controlinstructions; confirming, e.g., by the safety control subsystem, thelayout scheme and MRIU control instructions; and sending, e.g., by theinformation transmission subsystem, the layout scheme and MRIU controlinstructions to IRIS and/or MRIU.

In some embodiments, methods comprise backing up, by a data managementsubsystem, the service request.

In some embodiments, methods comprise providing a Mobile IntelligentRoadside Infrastructure System (MIRIS) comprising a Mobile RoadsideIntelligent Unit (MRIU); receiving, by an information transmissionsubsystem, a service request sent by an IRIS or a MRIU; and analyzing,by a mobile service subsystem, the specific working scenario of theservice request. In some embodiments, methods further comprisedetermining, e.g., by the mobile service subsystem, that the MIRIScannot provide services in the specific working scenario; generating,e.g., by the mobile service subsystem, a command that the MIRIS cannotmeet the service requirements; transmitting the command to theinformation transmission subsystem; and sending, e.g., by theinformation transmission subsystem, the command to IRIS and/or MRIUindicating that MIRIS cannot meet the service requirements.

In some embodiments, methods further comprise determining, e.g., by themobile service subsystem, that the MIRIS can provide services in thespecific working scenario; selecting, e.g., by the mobile servicesubsystem, work modules according to the specific service requirements;generating a layout scheme and MRIU control instructions; confirming,e.g., by the safety control subsystem, the layout scheme and MRIUcontrol instructions; and sending, e.g., by the information transmissionsubsystem, the layout scheme and MRIU control instructions to IRISand/or MRIU.

In some embodiments, methods comprise providing a Mobile IntelligentRoadside Infrastructure System (MIRIS) comprising a Mobile RoadsideIntelligent Unit (MRIU); receiving, by an intelligent communicationmodule, a deployment command from the RUMC; planning, by an intelligentcomputing module, a moving path and/or a moving speed for MRIU;selecting, e.g., by the intelligent decision control module, a movingpath and/or moving speed and sending the moving path and/or moving speedinformation to the intelligent mobile module; moving, e.g., by theintelligent mobile module, the MRIU according to the moving path and/ormoving speed; and monitoring, e.g., by the intelligent mobile module,the movement status of the MRIU. In some embodiments, planning a movingpath and/or a moving speed for MRIU comprises using and/or combiningprediction information and/or attribute information of the MRIU. In someembodiments, methods further comprise detecting, e.g., by theintelligent sensing module, obstacles in the moving path and/or abnormalconditions; and adjusting, e.g., by the intelligent computing moduleadjusts, the MRIU moving path based on real-time environment informationand/or the operating parameters of the MRIU to provide a new path. Insome embodiments, methods comprise determining, e.g., by the intelligentdecision control module, if the MRIU can reach the target position ontime according to the new path. In some embodiments, methods comprisedetermining, e.g., by the decision control module, that the MRIU cannotreach the task location on time according to the new path; and uploadingtask failure information to the RUMC. In some embodiments, methodsfurther comprise waiting, e.g., by the MRIU, for further instructionsfrom the RUMC. In some embodiments, methods comprise determining, e.g.,by the decision control module, that the MRIU can reach the tasklocation on time according to the new path; and moving, e.g., by theintelligent mobile module, the MRIU through the new path. In someembodiments, methods comprise confirming, e.g., by the intelligentdecision control module, the moving path and/or moving speed. In someembodiments, monitoring the movement status of the MRIU is monitoringthe movement status of the MRIU in real-time.

In some embodiments, systems comprise a computer and/or data storageprovided virtually (e.g., as a cloud computing resource). In particularembodiments, the technology comprises use of cloud computing to providea virtual computer system that comprises the components and/or performsthe functions of a computer as described herein. Thus, in someembodiments, cloud computing provides infrastructure, applications, andsoftware as described herein through a network and/or over the internet.In some embodiments, computing resources (e.g., data analysis,calculation, data storage, application programs, file storage, etc.) areremotely provided over a network (e.g., the internet; CAVH, IRIS, or CAHcommunications; and/or a cellular network). See, e.g., U.S. Pat. App.Pub. No. 20200005633, incorporated herein by reference.

Embodiments of the technology may also relate to an apparatus forperforming the operations herein. This apparatus may be speciallyconstructed for the required purposes and/or it may comprise ageneral-purpose computing device selectively activated or reconfiguredby a computer program stored in the computer. Such a computer programmay be stored in a non-transitory, tangible computer readable storagemedium or any type of media suitable for storing electronicinstructions, which may be coupled to a computer system bus.Furthermore, any computing systems referred to in the specification mayinclude a single processor or may be architectures employing multipleprocessor designs for increased computing capability.

Additional embodiments will be apparent to persons skilled in therelevant art based on the teachings contained herein.

BRIEF DESCRIPTION OF THE DRAWINGS

These and other features, aspects, and advantages of the presenttechnology will become better understood with regard to the followingdrawings.

FIG. 1 is a schematic drawing showing the components and architecture ofthe MIRIS. 101: Mobile Roadside Intelligent Unit (MRIU); 102: TrafficOperation Center (TOC); 103: Traffic Control Center (TCC); 104: TrafficControl Unit (TCU); 105: Roadside communication system.

FIG. 2 is a schematic drawing showing interactions between the MIRIS andother systems. 201: Roadside Intelligent Unit (RIU); 202: VehicleIntelligent Unit (VIU); 203: Data flow between MRIU and RIU; 204: Dataflow between MRIU and TCC/TCU; 205: Data flow between MRIU and TOC; 206:Data flow between MRIU and VIU.

FIG. 3A is a schematic drawing showing the components and architectureof the RUMC system. 301: Roadside Unit Management Control (RUMC) system;302: Information transmission subsystem; 303: Data management subsystem;304: Mobile service subsystem; 305: Security control subsystem; 306:Layout plan and control instructions; 307: Confirmed layout plan andcontrol instructions; 308: Service request; 309: Backup of layout schemeand control instruction; 310: Intelligent Road Infrastructure System(IRIS); 311: Service request reply for MRIU; 312: Service request fromthe MRIU; 313: Service request from the IRIS; 314: Service request replyfor IRIS; 315: Command that the MIRIS cannot satisfy the servicerequest.

FIG. 3B is a flow chart showing an exemplary method performed by theRUMC system.

FIG. 4 is a schematic drawing showing the mobile service subsystem inthe RUMC. 401: Dynamic deployment module; 402: Emergency service module;403: Auxiliary application module.

FIG. 5 is a schematic drawing of the MRIU components and architecture.501: Intelligent sensing module; 502: Intelligent computing module; 503:Intelligent decision control module; 504: Intelligent communicationmodule; 505: Intelligent mobile module; 506: Intelligent display module;507: Data transferred from MRIU to VIU; 508: Data obtained by MRIU fromVIU; 509: Traffic information collected by the intelligent sensingmodule; 510: Data flow from intelligent communication module tointelligent computing module; 511: Data flow from intelligent computingmodule to intelligent decision control module; 512: Data flow fromintelligent decision control module to intelligent communication module;513: Data flow from intelligent communication module to intelligentdecision control module; 514: Mobile path of the intelligent mobilemodule; 515: Movement status of MRIU; 516: Control instructions for theintelligent display module; 517: Data obtained by MRIU from TOC; 518:Data transferred from MRIU to TOC; 519: Data obtained by MRIU fromTCU/TCC; 520: Data transferred from MRIU to TCU/TCC; 521: Data obtainedby MRIU from RIU; 522: Data transferred from MRIU to RIU.

FIG. 6 is a schematic drawing of the intelligent computing modulecomponents and architecture. 601: Data storage unit; 602: Edge computingunit; 603: Route planning unit; 604: Traffic information provided to theedge computing unit; 605: Traffic information provided to the routeplanning unit; 606: Results of identifying, analyzing, and/or predictinga change of the external environment and/or moving state of the MRIU;607: Short-term prediction for the lane-level traffic flow parametersand the movement states of the connected automated vehicles; 608: Mobilescheme provided by the route planning unit.

FIG. 7 is a schematic drawing showing the intelligent decision controlmodule components and architecture. 701: Control unit.; 702:Decision-making unit; 703: Route selection unit; 704: Decisioninformation provided by the decision-making unit.

FIG. 8 is a flow chart of an exemplary method performed by the MRIUduring the movement process.

FIG. 9 is a flow chart of an exemplary management control methodperformed by the MRIU to assist RIU of the IRIS, e.g., to assist amalfunctioning RIU of the IRIS or to assist an RIU that is unable toprovide services to meet the requirements of the automated drivingfunction.

FIG. 10 is a flow chart of an exemplary management control methodperformed by the MRIU to assist an IRIS in an area without a RIU.

FIG. 11 is a flow chart of an exemplary management control methodperform by the MRIU to detect the layout location of RIU for a systemwithout IRIS.

It is to be understood that the figures are not necessarily drawn toscale, nor are the objects in the figures necessarily drawn to scale inrelationship to one another. The figures are depictions that areintended to bring clarity and understanding to various embodiments ofapparatuses, systems, and methods disclosed herein. Wherever possible,the same reference numbers will be used throughout the drawings to referto the same or like parts. Moreover, it should be appreciated that thedrawings are not intended to limit the scope of the present teachings inany way.

DETAILED DESCRIPTION

Provided herein is technology relating to automated driving andparticularly, but not exclusively, to a mobile intelligent roadinfrastructure technology configured to serve automated driving systemsby providing, supplementing, and/or enhancing autonomous drivingfunctions for connected automated vehicles under common and unusualdriving scenarios.

In this detailed description of the various embodiments, for purposes ofexplanation, numerous specific details are set forth to provide athorough understanding of the embodiments disclosed. One skilled in theart will appreciate, however, that these various embodiments may bepracticed with or without these specific details. In other instances,structures and devices are shown in block diagram form. Furthermore, oneskilled in the art can readily appreciate that the specific sequences inwhich methods are presented and performed are illustrative and it iscontemplated that the sequences can be varied and still remain withinthe spirit and scope of the various embodiments disclosed herein.

All literature and similar materials cited in this application,including but not limited to, patents, patent applications, articles,books, treatises, and internet web pages are expressly incorporated byreference in their entirety for any purpose. Unless defined otherwise,all technical and scientific terms used herein have the same meaning asis commonly understood by one of ordinary skill in the art to which thevarious embodiments described herein belongs. When definitions of termsin incorporated references appear to differ from the definitionsprovided in the present teachings, the definition provided in thepresent teachings shall control. The section headings used herein arefor organizational purposes only and are not to be construed as limitingthe described subject matter in any way.

Definitions

To facilitate an understanding of the present technology, a number ofterms and phrases are defined below. Additional definitions are setforth throughout the detailed description.

Throughout the specification and claims, the following terms take themeanings explicitly associated herein, unless the context clearlydictates otherwise. The phrase “in one embodiment” as used herein doesnot necessarily refer to the same embodiment, though it may.Furthermore, the phrase “in another embodiment” as used herein does notnecessarily refer to a different embodiment, although it may. Thus, asdescribed below, various embodiments of the invention may be readilycombined, without departing from the scope or spirit of the invention.

In addition, as used herein, the term “or” is an inclusive “or” operatorand is equivalent to the term “and/or” unless the context clearlydictates otherwise. The term “based on” is not exclusive and allows forbeing based on additional factors not described, unless the contextclearly dictates otherwise. In addition, throughout the specification,the meaning of “a”, “an”, and “the” include plural references. Themeaning of “in” includes “in” and “on.”

As used herein, the terms “about”, “approximately”, “substantially”, and“significantly” are understood by persons of ordinary skill in the artand will vary to some extent on the context in which they are used. Ifthere are uses of these terms that are not clear to persons of ordinaryskill in the art given the context in which they are used, “about” and“approximately” mean plus or minus less than or equal to 10% of theparticular term and “substantially” and “significantly” mean plus orminus greater than 10% of the particular term.

As used herein, disclosure of ranges includes disclosure of all valuesand further divided ranges within the entire range, including endpointsand sub-ranges given for the ranges.

As used herein, the suffix “-free” refers to an embodiment of thetechnology that omits the feature of the base root of the word to which“-free” is appended. That is, the term “X-free” as used herein means“without X”, where X is a feature of the technology omitted in the“X-free” technology. For example, a “calcium-free” composition does notcomprise calcium, a “mixing-free” method does not comprise a mixingstep, etc.

Although the terms “first”, “second”, “third”, etc. may be used hereinto describe various steps, elements, compositions, components, regions,layers, and/or sections, these steps, elements, compositions,components, regions, layers, and/or sections should not be limited bythese terms, unless otherwise indicated. These terms are used todistinguish one step, element, composition, component, region, layer,and/or section from another step, element, composition, component,region, layer, and/or section. Terms such as “first”, “second”, andother numerical terms when used herein do not imply a sequence or orderunless clearly indicated by the context. Thus, a first step, element,composition, component, region, layer, or section discussed herein couldbe termed a second step, element, composition, component, region, layer,or section without departing from technology.

As used herein, the word “presence” or “absence” (or, alternatively,“present” or “absent”) is used in a relative sense to describe theamount or level of a particular entity (e.g., component, action,element). For example, when an entity is said to be “present”, it meansthe level or amount of this entity is above a pre-determined threshold;conversely, when an entity is said to be “absent”, it means the level oramount of this entity is below a pre-determined threshold. Thepre-determined threshold may be the threshold for detectabilityassociated with the particular test used to detect the entity or anyother threshold. When an entity is “detected” it is “present”; when anentity is “not detected” it is “absent”.

As used herein, an “increase” or a “decrease” refers to a detectable(e.g., measured) positive or negative change, respectively, in the valueof a variable relative to a previously measured value of the variable,relative to a pre-established value, and/or relative to a value of astandard control. An increase is a positive change preferably at least10%, more preferably 50%, still more preferably 2-fold, even morepreferably at least 5-fold, and most preferably at least 10-foldrelative to the previously measured value of the variable, thepre-established value, and/or the value of a standard control.Similarly, a decrease is a negative change preferably at least 10%, morepreferably 50%, still more preferably at least 80%, and most preferablyat least 90% of the previously measured value of the variable, thepre-established value, and/or the value of a standard control. Otherterms indicating quantitative changes or differences, such as “more” or“less,” are used herein in the same fashion as described above.

As used herein, the term “number” shall mean one or an integer greaterthan one (e.g., a plurality).

As used herein, a “system” refers to a plurality of real and/or abstractcomponents operating together for a common purpose. In some embodiments,a “system” is an integrated assemblage of hardware and/or softwarecomponents. In some embodiments, each component of the system interactswith one or more other components and/or is related to one or more othercomponents. In some embodiments, a system refers to a combination ofcomponents and software for controlling and directing methods. Forexample, a “system” or “subsystem” may comprise one or more of, or anycombination of, the following: mechanical devices, hardware, componentsof hardware, circuits, circuitry, logic design, logical components,software, software modules, components of software or software modules,software procedures, software instructions, software routines, softwareobjects, software functions, software classes, software programs, filescontaining software, etc., to perform a function of the system orsubsystem. Thus, the methods and apparatus of the embodiments, orcertain aspects or portions thereof, may take the form of program code(e.g., instructions) embodied in tangible media, such as floppydiskettes, CD-ROMs, hard drives, flash memory, or any othermachine-readable storage medium wherein, when the program code is loadedinto and executed by a machine, such as a computer, the machine becomesan apparatus for practicing the embodiments. In the case of program codeexecution on programmable computers, the computing device generallyincludes a processor, a storage medium readable by the processor (e.g.,volatile and non-volatile memory and/or storage elements), at least oneinput device, and at least one output device. One or more programs mayimplement or utilize the processes described in connection with theembodiments, e.g., through the use of an application programminginterface (API), reusable controls, or the like. Such programs arepreferably implemented in a high-level procedural or object-orientedprogramming language to communicate with a computer system. However, theprogram(s) can be implemented in assembly or machine language, ifdesired. In any case, the language may be a compiled or interpretedlanguage, and combined with hardware implementations.

As used herein, the term “long-tail” scenario, event, environment, etc.refers to a scenario, event, environment, etc. that occurs at a lowfrequency and/or a scenario, event, environment, etc. that is predictedto occur with a low probability. Exemplary long-tail scenarios, events,and/or environments include, but are not limited to, vehicle accidents;special events (e.g., sports events, hazard evacuation, etc.);construction and/or work zones; extreme and/or adverse weather (e.g.,snowstorm, icy road, heavy rain, etc.); hazardous roads (e g animals onroads, rough roads, gravel, bumpy edges, uneven expansion joints, slicksurfaces, standing water, debris, uphill grade, downhill grade, sharpturns, no guardrails, narrow road, narrow bridge, etc.); unclear roadmarkings, unclear signing, and/or unclear geometric designs; highdensity of pedestrians and/or bicycles.

As used herein, the term “automated driving system” (abbreviated “ADS”)refers to a system that performs driving tasks (e.g. lateral andlongitudinal control of the vehicle) for a vehicle and thus allows avehicle to drive with reduced human control of driving tasks and/orwithout human control of driving tasks. The technology described hereinmay be provided to support and/or interact with various types ofexemplary ADS, including a road-based ADS, a CAV-based ADS, acloud-based ADS, and/or a high-precision map ADS. As used herein, theterm “road-based ADS” refers to an ADS in which the automated drivingsensing functions, prediction functions, decision-making functions, andcontrol functions are mainly provided and/or supported by theintelligent roadside infrastructure (e.g., a CAVH system). As usedherein, the term “CAV-based ADS” refers to an ADS in which automateddriving sensing functions, prediction functions, decision-makingfunctions, and control functions the are mainly provided and/orsupported by the on-board equipment of a CAV. As used herein, the term“cloud-based ADS” refers to an ADS in which the automated drivingsensing functions, prediction functions, decision-making functions, andcontrol functions are mainly provided and/or supported by a cloudplatform (e.g., a cloud platform provided by a vendor such as, e.g.,Microsoft Azure, Amazon Web Service, or Google Cloud). As used herein,the term “high precision map-based ADS” refers to an ADS in which theautomated driving sensing functions, prediction functions,decision-making functions, and control functions are provided and/orsupported by a high precision map system and high precision mapapplications (e.g., the high precision map system provides integratedautomated driving functions), e.g., as provided by a vendor such as,e.g., Here, TomTom, or OpenStreet Map.

As used herein, the term “Connected Automated Vehicle Highway System”(“CAVH System”) refers to a comprehensive system (e.g., an ADS)providing full vehicle operations and control for connected andautomated vehicles (CAV), and, more particularly, to a systemcontrolling CAVs by sending individual vehicles with detailed andtime-sensitive control instructions for vehicle following, lanechanging, route guidance, and related information. A CAVH systemcomprises sensing, communication, and control components connectedthrough segments and nodes that manage an entire transportation system.CAVH systems comprise four control levels: vehicle; roadside unit (RSU),which, in some embodiments, is similar to or the same as a roadsideintelligent unit (RIU); traffic control unit (TCU); and traffic controlcenter (TCC). See U.S. Pat. Nos. 10,380,886; 10,867,512; and/or10,692,365, each of which is incorporated herein by reference.

As used herein, the term “Intelligent Road Infrastructure System”(“IRIS”) refers to a system that facilitates vehicle operations andcontrol for CAVH systems. See U.S. Pat. Nos. 10,867,512 and/or10,692,365, each of which is incorporated herein by reference. In someembodiments, an IRIS provides transportation management and operationsand individual vehicle control for connected and automated vehicles(CAV). For example, in some embodiments, an IRIS provides a system forcontrolling CAVs by sending individual vehicles with customized,detailed, and time-sensitive control instructions and trafficinformation for automated vehicle driving, such as vehicle following,lane changing, route guidance, and other related information.

As used herein, the term “GPS” refers to a global navigation satellitesystem (GNSS) that provides geolocation and time information to areceiver. Examples of a GNSS include, but are not limited to, the GlobalPositioning System developed by the United States, Differential GlobalPositioning System (DGPS), BeiDou Navigation Satellite System (BDS)System, GLONASS Global Navigation Satellite System), European UnionGalileo positioning system, the NavIC system of India, and theQuasi-Zenith Satellite System (QZSS) of Japan.

As used herein, the term “vehicle” refers to any type of poweredtransportation device, which includes, and is not limited to, anautomobile, truck, bus, motorcycle, or boat. The vehicle may normally becontrolled by an operator or may be unmanned and remotely orautonomously operated in another fashion, such as using controls otherthan the steering wheel, gear shift, brake pedal, and accelerator pedal.

As used herein, the term “automated vehicle” (abbreviated as “AV”)refers to an automated vehicle in an automated mode, e.g., at any levelof automation (e.g., as defined by SAE International Standard J3016,“Taxonomy and Definitions for Terms Related to Driving AutomationSystems for On-Road Motor Vehicles” (published in 2014 (J3016_201401)and as revised in 2016 (J3016_201609) and 2018 (J3016_201806), each ofwhich is incorporated herein by reference)).

As used herein, the term “scene” refers to an environment in which avehicle operates or in which an object sensed by the ADS (e.g., CAVHsystem) operates and/or is present. In some embodiments, a “scene” is aview of an object or of a volume of space from a particular point andlooking in a particular direction in three-dimensional space. In someembodiments, a “scene” comprises static and/or dynamic objects sensed bythe ADS, MIRIS, IRIS, and/or CAVH system. In some embodiments, staticand/or dynamic objects in a scene are identified by coordinates withinthe scene. In some embodiments, the technology provides (e.g.,constructs) a scene that is a virtual model or reproduction of the scenesensed by the ADS, MIRIS, IRIS, and/or CAVH system. Accordingly, in someembodiments, a “scene” (e.g., the environment sensed by a vehicle and/orthe composite of information sensed by an ADS, MIRIS, IRIS, or CAVHsystem describing the environment of the vehicle) changes as a functionof time (e.g., as a function of the movement of vehicles and/or objectsin the scene). In some embodiments, a “scene” for a particular vehiclechanges as a function of the motion of the vehicle through athree-dimensional space (e.g., change in location of a vehicle inthree-dimensional space).

As used herein, the term “allocate”, “allocating”, and similar termsreferring to resource distribution also include distributing, arranging,providing, managing, assigning, controlling, and/or coordinatingresources.

As used herein, the term “resource” refers to computational capacity(e.g., computational power, computational cycles, etc.); memory and/ordata storage capacity; sensing capacity; communications capacity (e.g.,bandwidth, signal strength, signal fidelity, etc.); and/or electricalpower.

As used herein, the term “service” refers to a process, a function thatperforms a process, and/or to a component or module that is configuredto provide a function that performs a process.

As used herein, the term “connected vehicle” or “CV” refers to aconnected vehicle, e.g., configured for any level of communication(e.g., V2V, V2I, and/or I2V).

As used herein, the term “connected and autonomous vehicle” or “CAV”refers to an autonomous vehicle that is able to communicate with othervehicles (e.g., by V2V communication), with roadside intelligent units(RIU), traffic control signals, and/or other infrastructure (e.g., anADS or component thereof) or devices. That is, the term “connectedautonomous vehicle” or “CAV” refers to a connected autonomous vehiclehaving any level of automation (e.g., as defined by SAE InternationalStandard J3016 (2014)) and communication (e.g., V2V, V2I, and/or I2V).

As used herein, the term “data fusion” refers to integrating a pluralityof data sources to provide information (e.g., fused data) that is moreconsistent, accurate, and useful than any individual data source of theplurality of data sources.

As used herein, the term “configured” refers to a component, module,system, subsystem, etc. (e.g., hardware and/or software) that isconstructed and/or programmed to carry out the indicated function.

As used herein, the terms “determine,” “calculate,” “compute,” andvariations thereof, are used interchangeably to any type of methodology,processes, mathematical operation, or technique.

As used herein, the term “reliability” refers to a measure (e.g., astatistical measure) of the performance of a system without failureand/or error. In some embodiments, reliability is a measure of thelength of time and/or number of functional cycles a system performswithout a failure and/or error.

As used herein, the term “support” when used in reference to one or morecomponents of an ADS, CAVH, CAV, and/or a vehicle providing support toand/or supporting one or more other components of the ADS, CAVH, CAV,and/or a vehicle refers to, e.g., exchange of information and/or databetween components and/or levels of the ADS, CAVH, CAV, and/or avehicles; sending and/or receiving instructions between componentsand/or levels of the ADS, CAVH, CAV, and/or a vehicles; and/or otherinteraction between components and/or levels of the ADS, CAVH, CAV,and/or a vehicles that provide functions such as information exchange,data transfer, messaging, and/or alerting.

As used herein, the term “ADS component” or “component of an ADS” refersindividually and/or collectively to one or more of components of an ADSand/or a CAVH system, e.g., a VIU, RIU, TCC, TCU, TCC/TCU, TOC, CAV, asupporting subsystem, and/or a cloud component.

As used herein, the term “roadside intelligent unit” (abbreviated “RIU”)may refer to one RIU, a plurality of RIU, and/or a network of RIU.

As used herein, the term “mobile roadside intelligent unit” (abbreviated“MRIU”) refers to a mobile RIU. In some embodiments, the MRIU isprovided on a mobile component and/or platform comprising wheels,continuous track, etc. (e.g., for deployment on land). For example, insome embodiments, the MRIU is deployed on a manual vehicle; an unmannedvehicle; on specialized infrastructure (e.g., a dedicated path, road, orrails), and/or on a mobile robot. In some embodiments, the MRIU isprovided on a platform for deployment in the air (e.g., comprisingwings, a propeller, a balloon, etc.). For example, in some embodiments,the MRIU is provided on a platform comprising an unmanned aerial vehicleor drone. In some embodiments, the MRIU is provided for deployment inthe water (e.g., comprising a buoyant component, a propeller, etc.)Exemplary deployment locations for an MRIU include, but are not limitedto, positions where an RIU may be deployed. In some embodiments,exemplary locations for an MRIU include, but are not limited to, at aroadside; on, in, and/or above a highway; at an on ramp; at an off ramp;at an intersection; on a roadside building; at a bridge; at a tunnel; ata roundabout; at a bus stop; at a parking spot; at a railway crossing;at a grade crossing; in a school area; and/or at a testing ground.

As used herein, the term “critical point” refers to a portion or regionof a road that is identified as appropriate to be provided embodimentsof the function allocation technology provided herein. In someembodiments, a critical point is categorized as a “static criticalpoint” and in some embodiments, a critical point is categorized as a“dynamic critical point”. As used herein, a “static critical point” is apoint (e.g., region or location) of a road that is a critical pointbased on identification of road and/or traffic conditions that aregenerally constant or that change very slowly (e.g., on a time scalelonger than a day, a week, or a month) or only by planned reconstructionof infrastructure. As used herein, a “dynamic critical point” is a point(e.g., region or location) of a road that is a critical point based onidentification of road conditions that change (e.g., predictably or notpredictably) with time (e.g., on a time scale of an hour, a day, a week,or a month). Critical points based on historical crash data, trafficsigns, traffic signals, traffic capacity, and road geometry areexemplary static critical points. Critical points based on trafficoscillations, real-time traffic management, or real-time trafficincidents are exemplary dynamic critical points.

In some embodiments, critical points are identified using, e.g.,historical crash data (e.g., the top 20% (e.g., top 15-25% (e.g., top15, 16, 17, 18, 19, 20, 21, 22, 23, 24, or 25%)) most frequent crashpoints in a road system are identified as critical points); trafficsigns (e.g., where certain traffic signs (e.g., accident-prone areas)are detected are identified as critical points); traffic capacity (e.g.,the top 20% (e.g., top 15-25% (e.g., top 15, 16, 17, 18, 19, 20, 21, 22,23, 24, or 25%)) highest traffic capacity areas are identified ascritical points); road geometry (e.g., roads with critical road geometry(e.g., curves, blind spots, hills, intersections (e.g., signalizedintersections, stop sign intersections, yield sign intersections),roundabouts) are identified as critical points); traffic oscillation(e.g., points with significant traffic oscillations are identified ascritical points); real-time traffic management (e.g., points withpotential traffic management are identified as critical points); and/orreal-time traffic incident (e.g., points with traffic incidents (e.g.,accident, crash, congestion, construction or maintenance,weather-related event, etc.) or vehicle malfunction are identified ascritical points).

As used herein, the terms “microscopic”, “mesoscopic”, and “macroscopic”refer to relative scales in time and space. In some embodiments, thescales include, but are not limited to, a microscopic level relating toindividual vehicles (e.g., longitudinal movements (car following,acceleration and deceleration, stopping and standing) and lateralmovements (lane keeping, lane changing)), a mesoscopic level relating toroad corridors and/or segments (e.g., special event early notification,incident prediction, merging and diverging, platoon splitting andintegrating, variable speed limit prediction and reaction, segmenttravel time prediction, and/or segment traffic flow prediction), and amacroscopic level relating to an entire road network (e.g., predictionof potential congestion, prediction of potential incidents, predictionof network traffic demand, prediction of network status, prediction ofnetwork travel time). In some embodiments, a time scale at a microscopiclevel is from 1 to 10 milliseconds and is relevant to tasks such asvehicle control instruction computation. In some embodiments, a timescale at a mesoscopic level is typically from 10 to 1000 millisecondsand is relevant to tasks such as incident detection and pavementcondition notification. In some embodiments, a time scale at amacroscopic level is longer than 1 second and is relevant to tasks suchas route computing.

As used herein, the automation and/or intelligence levels of vehicles(V), infrastructure (I), and system (S) are described with respect to an“intelligence level” and/or an “automation level”. In some embodiments,the vehicle intelligence and/or automation level is one of thefollowing: V0: No automation functions; V1: Basic functions to assist ahuman driver to control a vehicle; V2: Functions to assist a humandriver to control a vehicle for simple tasks and to provide basicsensing functions; V3: Functions to sense the environment in detail andin real-time and to complete relatively complicated driving tasks; V4:Functions to allow vehicles to drive independently under limitedconditions and sometimes with human driver backup; and V5: Functions toallow vehicles to drive independently without human driver backup underall conditions. As used herein, a vehicle having an intelligence levelof 1.5 (V1.5) refers to a vehicle having capabilities between vehicleintelligence 1 and vehicle intelligence level 2, e.g., a vehicle at V1.5has minimal or no automated driving capability but comprisescapabilities and/or functions (e.g., hardware and/or software) thatprovide control of the V1.5 vehicle by a CAVH system (e.g., the vehiclehas “enhanced driver assistance” or “driver assistance plus”capability).

In some embodiments, the infrastructure intelligence and/or automationlevel is one of the following: I0: No functions; I1: Informationcollection and traffic management wherein the infrastructure providesprimitive sensing functions in terms of aggregated traffic datacollection and basic planning and decision making to support simpletraffic management at low spatial and temporal resolution; I2: I2X andvehicle guidance for driving assistance, wherein, in addition tofunctions provided in I1, the infrastructure realizes limited sensingfunctions for pavement condition detection and vehicle kinematicsdetection, such as lateral and/or longitudinal position, speed, and/oracceleration, for a portion of traffic, in seconds or minutes; theinfrastructure also provides traffic information and vehicle controlsuggestions and instructions for the vehicle through I2X communication;I3: Dedicated lane automation, wherein the infrastructure providesindividual vehicles with information describing the dynamics ofsurrounding vehicles and other objects on a millisecond time scale andsupports full automated driving on CAVH-compatible vehicle dedicatedlanes; the infrastructure has limited transportation behavior predictioncapability; I4: Scenario-specific automaton wherein the infrastructureprovides detailed driving instructions for vehicles to realize fullautomated driving in certain scenarios and/or areas, such as locationscomprising predefined geo-fenced areas, where the traffic is mixed(e.g., comprises automated and non-automated vehicles); essentialvehicle-based automation capability, such as emergency braking, isprovided as a backup system in case the infrastructure fails; and I5:Full infrastructure automation wherein the infrastructure provides fullcontrol and management of individual vehicles under all scenarios andoptimizes a whole road network where the infrastructure is deployed;vehicle automation functionality is not necessary provided as a backup;full active safety functions are available.

In some embodiments, the system intelligence and/or automation level isone of the following: S0: no function; S1: the system provides simplefunctions for individual vehicles such as cruise control and passivesafety function; the system detects the vehicle speed, location, anddistance; S2: the system comprises individual intelligence and detectsvehicle functioning status, vehicle acceleration, and/or traffic signsand signals; individual vehicles make decisions based on their owninformation and have partially automated driving to provide complicatedfunctions such as assisting vehicle adaptive cruise control, lanekeeping, lane changing, and automatic parking; S3: the system integratesinformation from a group of vehicles and behaves with ad-hocintelligence and prediction capability, the system has intelligence fordecision making for the group of vehicles and can complete complicatedconditional automated driving tasks such as cooperative cruise control,vehicle platooning, vehicle navigation through intersections, merging,and diverging; S4: the system integrates driving behavior optimallywithin a partial network; the system detects and communicates detailedinformation within the partial network and makes decisions based on bothvehicle and transportation information within the network and handlescomplicated, high level automated driving tasks, such as navigatingtraffic signal corridors, and provides optimal trajectories for vehicleswithin a small transportation network; S5: vehicle automation and systemtraffic automation, wherein the system optimally manages an entiretransportation network; the system detects and communicates detailedinformation within the transportation network and makes decisions basedon all available information within the network; the system handles fullautomated driving tasks, including individual vehicle tasks andtransportation tasks, and coordinates all vehicles to manage traffic.

In some embodiments, the system dimension is dependent on the vehicleand infrastructure dimensions, e.g., as represented by the followingequation (S=system automation; V=vehicle intelligence; andI=infrastructure intelligence):

S=f(V,I)

In some embodiments, vehicle intelligence is provided by and/or relatedto the CAV Subsystem and the infrastructure intelligence is provided byand/or related to the CAH Subsystem. One of ordinary skill in the artmay refer to SAE International Standard J3016, “Taxonomy and Definitionsfor Terms Related to Driving Automation Systems for On-Road MotorVehicles” (published in 2014 (J3016_201401) and as revised in 2016(J3016_201609) and 2018 (J3016_201806)), which provides additionalunderstanding of terms used in the art and herein.

DESCRIPTION

The present technology provides a Mobile Intelligent Road InfrastructureSystem (MIRIS) and related methods (e.g., management methods) configuredto serve automated driving systems (ADS) (e.g., connected and automatedvehicle highway (CAVH) system). The MIRIS comprises one or more of thefollowing physical subsystems: (1) Mobile Roadside Intelligent Unit(MRIU); (2) Traffic Operation Center (TOC); (3) Traffic Control Center(TCC) and Traffic Control Unit (TCU); and/or (4) roadside communicationsystem. In some embodiments, the MIRIS is supported by one or more ofthe following systems of the ADS or CAVH: a multi-level cloud platform(e.g., comprising microscopic cloud, mesoscopic cloud, and/ormacroscopic cloud), a high-precision mapping system, an energy supplysystem, and/or information security system.

In some embodiments, the ADS is and/or comprises one or more of aroad-based ADS, CAV-based ADS, cloud-based ADS, and/or high precisionmap-based ADS.

In some embodiments, the MIRIS is configured to serve intelligentvehicles having an intelligence levels of V1, V1.5, V2, V3, V4, and/orV5, e.g., as defined by SAE International Standard J3016, “Taxonomy andDefinitions for Terms Related to Driving Automation Systems for On-RoadMotor Vehicles” (published in 2014 (J3016_201401) and as revised in 2016(J3016_201609) and 2018 (J3016_201806)), each of which is incorporatedherein by reference. In some embodiments, MIRIS receives data from avehicle (e.g., from a Vehicle Intelligent Unit (VIU) of a vehicle)and/or receives data collected by the MRIU. In some embodiments, theMIRIS generates vehicle control instructions and sends them to a vehicle(e.g., to a VIU of a vehicle).

In some embodiments, the MIRIS is configured to provide, supplement,enhance, exceed, improve, and/or replace the macroscopic, mesoscopic,and/or microscopic functions (e.g., sensing, prediction,decision-making, and/or control) for automated driving. In someembodiments, the MIRIS is configured to manage and control MRIU incomplex scenarios (e.g., changes of traffic flow, changes of drivingenvironment, emergencies, and other scenarios). In some embodiments,MIRIS is configured to provide and/or perform management and controlmethods for the MRIU, e.g., when a RIU of the IRIS malfunctions; when anRIU of the IRIS is failing; when a RIU of the IRIS is unable to provideadequate automated driving functions to support automated driving byvehicles (e.g., CAV); and/or when IRIS does not comprise RIU whereneeded to provide and/or support automated driving functions (e.g., IRIScomprises inadequate coverage by RIU to provide and/or support automateddriving functions (e.g., for RIU-free points, road segments, roads,regions, and/or geographic areas)). In some embodiments, the MIRISprovides management and control methods for individual RIU deployment,e.g., for points, road segments, roads, regions, and/or geographic areaswhen there is no IRIS deployed (e.g., in IRIS-free points, roadsegments, roads, regions, and/or geographic areas).

In some embodiments, the TOC provides mid-term and long-term trafficstate prediction, traffic management, traffic planning, and/ordecision-making. In some embodiments, the TOC provides mid-term andlong-term traffic state prediction, traffic management, trafficplanning, and/or decision-making based on the multi-level cloud platform(e.g., based on the macroscopic cloud system of the multi-level cloudplatform). In some embodiments, the TOC comprises a Roadside UnitManagement Control (RUMC) system. In some embodiments, the RUMC isconfigured to formulate control strategies according to real-timetraffic status and/or demands; and/or is further configured to adjustthe positions of MRIUs to provide automated driving functions in variousscenarios.

In some embodiments, the MRIU is configured to exchange data andinformation with RIU, TCU, TCC, TOC, and/or vehicles (e.g., a VIU).

In some embodiments, the MIRIS comprises a roadside communicationssystem. In some embodiments, the roadside communications systemcomprises components configured to provide wired and/or wirelesscommunications. In some embodiments, the roadside communication systemprovides wired or wireless data transmission between systems, e.g.,using communication modes such as, e.g., LTE-V2X, 5G, 6G, 7G. In someembodiments, the roadside communications system is configured to supportvarious types of I2X (Infrastructure-to-Everything) applications and/orcommunications.

In some embodiments, the multi-level cloud platform comprises cloudcomponents at a range of scales, e.g., a macroscopic cloud, mesoscopiccloud, and/or microscopic cloud. In some embodiments, the cloud platform(e.g., macroscopic cloud, mesoscopic cloud, and/or microscopic cloud)are configured to provide computing and/or data storage resources (e.g.,capacity) for the TOC, TCC, and TCU. In some embodiments, themacroscopic cloud, mesoscopic cloud, and/or microscopic cloud areconfigured to provide computing and/or data storage resources (e.g.,capacity) for the TOC, TCC, and TCU, respectively.

In some embodiments, the MIRIS comprises a high-precision map system. Insome embodiments, the MIRIS is supported by a high-precision map system,e.g., provided by the ADS (e.g., CAVH system). In some embodiments, thehigh precision map system is configured to provide positioning and/ormapping services for the RUMC and/or MRIU.

In some embodiments, the MIRIS comprises an energy supply system. Insome embodiments, the MIRIS is supported by an energy supply system,e.g., provided by the ADS (e.g., CAVH system). In some embodiments, theenergy supply system is configured to provide electrical power for theoperation of the MIRIS and/or component systems of the MIRIS and/or ADS(e.g., CAVH system).

In some embodiments, the MIRIS comprises an information security system.In some embodiments, the MIRIS is supported by an information securitysystem, e.g., provided by the ADS (e.g., CAVH system). In someembodiments, the information security system is configured to maximizecommunication security and/or information storage security of the MIRISand/or component systems of the MIRIS and/or ADS (e.g., CAVH system).

In some embodiments, the RUMC system comprises an Informationtransmission subsystem, a Data management subsystem, a Mobile servicesubsystem, and/or a Security control subsystem. The informationtransmission subsystem is configured to provide exchange of information,data, and control instructions (e.g., MRIU control instructions) amongthe RUMC systems, multi-layer cloud platforms, MRIU, and/or IRIS (e.g.,the information transmission subsystem is configured to exchangeinformation, transmit data, and distribute control instructions (e.g.,vehicle control instructions and/or MRIU control instructions) among theRUMC systems, multi-layer cloud platforms, MRIU, and IRIS). The datamanagement subsystem is configured to store the quantity, position,state, energy consumption, and/or other parameter information of MRIU(e.g., describing the state and/or function of the MRIU) in the MIRIS.The data management subsystem is configured to record data of theroadway driving environment, real-time MRIU data, the historicalmovement and/or placement strategies for the MRIU, and/or the historicalmovement and/or placement of the MRIU. Further, in some embodiments, thedata management subsystem is configured to perform data backup, e.g., toprovide storage and backup while adjusting the position of MRIU in theroad network and/or to store movement plans generated by the mobileservice subsystem. The mobile service subsystem is configured to analyzemission requirements. For example, in some embodiments, the mobileservice system formulates a MRIU deployment plan (e.g., comprising MRIUlocations and/or movements) according to the corresponding roadway sceneand MRIU parameters recorded in the data management subsystem (e.g.,MRIU position, MRIU status, and/or MRIU energy consumption information).In some embodiments, the mobile service subsystem generates specificMRIU control strategies and/or task instructions to provide an MRIU at aspecific location and/or to adjust the location of an MRIU. The securitycontrol subsystem is configured to confirm mobile commands provided bythe mobile service subsystem and to send commands to the informationtransmission subsystem for execution, thus maximizing the accuracy andcontrol security for the MRIU.

In some embodiments, the RUMC is configured to perform RUMC methods. Forexample, in some embodiments, RUMC methods comprise receiving (e.g., bythe information transmission subsystem) a service request sent by IRISor MRIU; backing up (e.g., by the data management subsystem) therequest; analyzing (e.g., by the mobile service subsystem) the specificworking scenario of the request; and judging (e.g., by the mobileservice subsystem) if the MIRIS can provide adequate services for thescenario and automated driving task. In some embodiments, if the judgingstep indicates that the MIRIS can provide adequate services in thescenario for the automated driving task, methods further comprisegenerating (e.g., by the mobile service subsystem) a MRIU layout schemeand MRIU control instructions (e.g., providing the locations of MRIUand/or MRIU control instructions to place and/or move the MRIU);confirming (e.g., by the safety control subsystem) the MRIU layoutscheme and MRIU control instructions; and sending the MRIU layout schemeand MRIU control instructions (e.g., providing the locations of MRIUand/or MRIU control instructions to place and/or move the MRIU) to theinformation transmission subsystem. In some embodiments, if the judgingstep indicates that the MIRIS cannot provide adequate services in thescenario for the automated driving task, methods further comprisegenerating (e.g., by the mobile service subsystem) a command indicatingthat the MIRIS cannot meet the service requirements; transmitting thecommand to the information transmission subsystem; and transmitting(e.g., by the information transmission subsystem) the received commandto the IRIS or MRIU.

In some embodiments, the mobile service subsystem comprises a dynamicdeployment module, an emergency service module, and/or an auxiliaryapplication module. The dynamic deployment module is configured tobalance service provided by the MIRIS and/or ADS (e.g., CAVH system) anddemands of vehicles (e.g., CAV) and/or traffic for service provided bythe MIRIS and/or ADS (e.g., CAVH system). Accordingly, in someembodiments, the dynamic deployment module is configured to analyzeMIRIS and/or ADS (e.g., CAVH system) service capabilities and demands ofvehicles (e.g., CAV) for MIRIS and/or ADS (e.g., CAVH system) services.In some embodiments, the dynamic deployment module is configured toanalyze historical MIRIS and/or ADS (e.g., CAVH system) servicecapabilities and demands of vehicles (e.g., CAV) for MIRIS and/or ADS(e.g., CAVH system) services and/or to predict MIRIS and/or ADS (e.g.,CAVH system) service capabilities and demands of vehicles (e.g., CAV)for MIRIS and/or ADS (e.g., CAVH system) services. In some embodiments,the dynamic deployment module is configured to optimize servicesprovided by the MIRIS and/or ADS (e.g., CAVH system) based on thedemands of vehicles (e.g., CAV) and/or traffic for service provided bythe MIRIS and/or ADS (e.g., CAVH system). In some embodiments, thedynamic deployment module is configured to receive data describingreal-time and/or predicted changes in CAV traffic flow, e.g., fordifferent time periods and/or for different geographic areas. In someembodiments, the dynamic deployment module is configured to sense (e.g.,perceive), recognize, and/or analyze a scenario and/or a combination ofscenarios and generate MRIU deployment plans, e.g., to adjust thequantity and/or position of MRIUs in the road network. Accordingly, thedynamic deployment module is configured to provide and manage a dynamicbalance between service capabilities (e.g., service provided by theMIRIS and/or ADS (e.g., CAVH system)) and traffic demand (e.g., demandsof vehicles (e.g., CAV) and/or traffic for service provided by the MIRISand/or ADS (e.g., CAVH system)).

In some embodiments, the dynamic deployment module is module isconfigured to provide and manage a dynamic balance between servicecapabilities and traffic demands in environments and/or scenarioscomprising one or more of (e.g., combinations of) different types ofroads and road sections (e.g., freeways, expressways, entrances, exits,main sections, service areas, urban roads, urban expressways, arterialroads, secondary roads, access roads, and intersections); differenttypes of intersections (e.g., normal intersection, three-dimensionalintersections); different numbers of lanes (e.g., two-way four-lane,two-way six-lane, two-way eight-lane); different types of lanes (e.g.,mixed traffic lanes, bus lanes, large passenger car lanes, large trucklanes, commuter lanes); different time periods (e.g., regular times,morning peak traffic, evening peak traffic, holidays, special events);different traffic states (e.g., free flow, synchronous flow, wide movingjam); and/or combinations of any of the foregoing.

In some embodiments, the emergency service module is configured tomanage a “long tail” scenario for autonomous driving. Specifically, theemergency service module is configured to detect and recognize emergencyor “long tail” scenarios, e.g., severe weather, traffic incident,construction, special event, and/or social security incident. In someembodiments, the emergency service module generates a MRIU managementand control strategy in response to emergency scenarios and supplementsor enhances the sensing, prediction, decision-making, and/or vehiclecontrol function of the ADS (e.g., CAVH system) in special scenarios(e.g., long-tail scenarios).

In some embodiments, the emergency service module is configured tocontrol vehicles and/or manage traffic for a scenario comprising one ormore of (e.g., combinations of) severe weather (e.g., ice, snow, densefog, heavy rain, hail, typhoon, tornado, sandstorm); complex roadenvironment (e.g., long tunnels, steep grade (e.g., ascent or descent),multiple bends (e.g., curvy road, hairpin turns), unmarked roads, visualblind spots (e.g., at intersections), areas comprising high quantitiesand/or concentrations of pedestrians and/or bicycle traffic; animalcrossing; environmental incidents (e.g., road collapse, landslide, flood(road washout), rockslide, tree across road, mudslide, earthquake, powerfailure, signal interference, cyber-attack); construction (e.g.,construction of new roads, road repairs, maintenance, bridge repairs,tunnel repairs); traffic incidents (e.g., vehicle collision, scratch,rollover, fire, and other traffic accidents); special events (e.g.,concerts, theatre performances, operas, sports events, exhibitions,community events, and other events that require traffic control andmanagement); social security events (e.g., toxic gas leakage, chemicalspill, emergency evacuation, rescue of wounded, criminal arrests,roadblock, checkpoint, and other social security events that causetraffic condition changes); and/or combinations of any of the foregoing.In some embodiments, the emergency service module is configured tocontrol vehicles and/or manage traffic for a scenario comprising anincident that causes an RIU and/or a MRIU to fail and/or to provideinadequate support for automated driving tasks for the scenario. In someembodiments, the emergency service module is configured to controlvehicles and/or manage traffic for a scenario comprising a constructionactivity that causes the suspension of fixed RIU services. In someembodiments, the emergency service module is configured to controlvehicles and/or manage traffic for a scenario comprising a trafficaccident that causes damage to the IRIS (e.g., IRIS infrastructure).

In some embodiments, the auxiliary application module is configured togenerate MRIU control strategies and/or schemes for additional servicerequirements provided to the automated driving system (e.g., assistingin deploying fixed RIU in the IRIS, updating high-precision map system,and/or collecting traffic information).

In some embodiments, the MRIU comprises an Intelligent sensing module;an Intelligent communication module; an Intelligent computing module; anIntelligent decision control module; an Intelligent mobile module;and/or an Intelligent display module. In some embodiments, theintelligent sensing module is configured to provide information inputfor controlling vehicles and/or managing traffic by the ADS (e.g., CAVHsystem) and/or providing information support for moving MRIU. Theintelligent sensing module is configured to perform a sensing functioncomprising one or more of (e.g., combinations of) an environment sensingfunction (e.g., for detecting and/or monitoring traffic flow, vehiclemovement parameters, road condition, road alignment, weather, andobstacle information) and/or a mobile state sensing function (e.g., forsensing parameters of MRIU (e.g., MRIU longitude, MRIU latitude, MRIUmoving speed, and/or MRIU acceleration). In some embodiments, thesensing function comprises use of data provided by a sensor (e.g.,radar, camera, lidar, and/or weather sensors). In some embodiments, themobile state sensing function comprises use of data provided by a GNSSand/or an inertial navigation system.

In some embodiments, the intelligent communication module providesand/or supports multi-mode communication, e.g., using LTE-V2X, Wi-Fi,GPS/BeiDou, 4G, 5G, 6G, and/or 7G. In some embodiments, the intelligentcommunication module provides low-delay (low-latency), high-reliability,and/or high-density data exchange among MRIU and other infrastructurecomponents, e.g., RIU; TCU; TCC; TOC; and/or VIU.

In some embodiments, the intelligent computing module is configured toprovide data fusion, data storage, and/or data feature extraction, e.g.,for sensing data and/or for multi-source sensing data. In someembodiments, the intelligent computing module is configured to predicttraffic flow state (e.g., on a microscopic and/or mesoscopic time scale)and to optimize a moving speed and/or path for MRIU in real-time. Insome embodiments, the intelligent competent module comprises one or moreof (e.g., combinations of) a data storage unit (e.g., configured tostore traffic information (e.g., collected by the intelligent sensingmodule and processed by the multi-level cloud platform), backup taskinstructions (e.g., sent by the RUMC); and/or record the workingparameters of the MRIU); an edge computing unit (e.g., configured toperform data fusion and/or data feature extraction for the trafficinformation; predict (e.g., on a microscopic and/or mesoscopic timescale) lane traffic flow parameters and/or the movement state of theconnected automated vehicles; and/or supplement the computing capacityof the ADS system); and/or a route planning unit (e.g., configured toplan a moving path and/or trajectory of MRIU; and optimize the movingspeed and/or trajectory of MRIU). In some embodiments, the edgecomputing unit is configured to identify, analyze, and/or predict achange of the external environment and/or the moving state of the MRIU.

In some embodiments, the intelligent decision control module isconfigured to determine and/or provide vehicle control and trafficmanagement strategies, to generate vehicle control instructions; and/orto distribute vehicle control information to CAV (e.g., CAV at anyintelligence level). In some embodiments, the intelligent decisioncontrol module is configured to determine the moving speed and/or pathof MRIU. In some embodiments, the intelligent decision control modulecomprises one or more of (e.g., combinations of) a decision-making unit(e.g., configured to provide and/or improve the decision-making functionof CAV (e.g., CAV at any intelligence level), e.g., under variousscenarios; and/or to provide traffic management decisions under variousspecial scenarios); a control unit (e.g., configured to generate vehiclecontrol instructions for CAV (e.g., CAV at any intelligence level);and/or enhance and/or maximize the safety of CAV in various unusualscenarios); and/or a route selection unit (e.g., configured to determinea moving path; and/or to determine if the planned path is adequate toprovide automated driving for the automated driving task assigned by theRUMC).

In some embodiments, the intelligent mobile module is configured torelocate the MRIU (e.g., according to the speed and path determinedand/or provided by the intelligent decision control module); monitor themovement status and/or energy consumption of the MRIU (e.g., inreal-time); and/or provide feedback information (e.g., describing afailure or delay) to the intelligent decision control module (e.g., inreal-time).

In some embodiments, the intelligent display module is configured toassist the driving of CAV (e.g., CAV at any intelligence level (e.g.,CAV at a low intelligence level (e.g., V1, V1.5, or V2) and/or CAV at ahigh intelligence level (e.g., V3, V4, or V5) and having a VIUfailure)).

In some embodiments, the technology provides methods for moving an MRIU.In some embodiments, methods for moving an MRIU comprise receiving(e.g., by the intelligent communication module) a deployment commandfrom the RUMC; planning (e.g., by the intelligent computing module) theMRIU moving path and/or the MRIU moving speed; selecting (e.g., by theintelligent decision control module) and optionally confirming (e.g., bythe intelligent decision control module) the MRIU moving path and/orMRIU moving speed; and sending the MRIU moving path and/or MRIU movingspeed to the intelligent mobile module. In some embodiments, methodscomprise moving (e.g., by the intelligent mobile module) an MRIUaccording to the calculated MRIU path and/or MRIU moving speed; andmonitoring (e.g., by the intelligent mobile module) the movement statusof MRIU (e.g., in real-time). In some embodiments, methods comprisedetecting (e.g., by the intelligent sensing module) the presence ofobstacles in the MRIU path and/or detecting (e.g., by the intelligentmobile module) abnormal conditions; and re-planning (e.g., by theintelligent computing module) the MRIU moving path. In some embodiments,methods comprise determining (e.g., by the intelligent decision controlmodule) if the MRIU can reach the task position on time according to thenew planning path. In some embodiments, methods comprise determining(e.g., by the intelligent decision control module) that the MRIU cannotreach the task location on time according to the new planning path;uploading (e.g., by the intelligent decision control module) taskfailure information to the RUMC; and, optionally, waiting (e.g., by theMRIU) for further MRIU control instructions from the RUMC. In someembodiments, methods comprise determining (e.g., by the intelligentdecision control module) that the MRIU can reach the task location ontime according to the new planning path; and moving (e.g., by theintelligent mobile module) the MRIU according to the updated MRIU pathto the desired target location for the MRIU.

In some embodiments, the technology provides a management control methodfor MRIU. In some embodiments, the MIRIS is configured to perform amanagement control method for MRIU. In some embodiments, the MIRISperforms a management control method when an RIU malfunctions, when anRIU is non-functional, and/or when an RIU cannot provide adequateautomated driving functions to vehicles (e.g., CAV). In someembodiments, management control methods comprise detecting (e.g., byIRIS) a failure (e.g., a partial failure or a complete failure) of anRIU and/or detecting an RUI that is not able to provide adequatefunctions for automated driving; and, optionally, adjusting (e.g.,reallocating resources) by the IRIS to provide adequate functions forautomated driving. In some embodiments, if the IRIS cannot adjust (e.g.,reallocate resources) to provide adequate functions for automateddriving, methods comprise sending (e.g., by IRIS) a service request tothe RUMC. In some embodiments, methods comprise determining (e.g., byRUMC) if MRIU are available for use by the ADS (e.g., CAVH system (e.g.,IRIS of the CAVH system)). If MRIU are available, methods compriseplanning (e.g., by the RUMC) a MRIU scheduling scheme; and sending MRIUmoving instructions and/or work tasks to the selected MRIU. Finally, insome embodiments, methods comprise moving MRIU to the specifiedlocation; and performing by the MRIU automated driving tasks, e.g., incooperation with the RIU. In some embodiments, if MRIU are not availablefor use by the ADS (e.g., CAVH system (e.g., IRIS of the CAVH system)),methods comprise reducing the intelligence level of the area (e.g.,regions where MRIU are not available for use by the ADS (e.g., CAVHsystem (e.g., IRIS of the CAVH system))).

In some embodiments, the technology provides a management control methodfor MRIU in locations where the IRIS has no RIU deployed (e.g., RIU-freepoint, road segments, roads, regions, etc.). In some embodiments, theMIRIS is configured to perform a management control method for MRIU inlocations where the IRIS has no RIU deployed (e.g., RIU-free points,road segments, roads, regions, etc.). In some embodiments, the MIRISperforms a management control method in locations where the IRIS has noRIU deployed (e.g., RIU-free points, road segments, roads, regions,etc.). In some embodiments, management control method in locations wherethe IRIS has no RIU deployed comprise detecting (e.g., by IRIS) aservice demand in the area without a RIU; and sending a service requestto the RUMC. In some embodiments, methods comprise determining (e.g., byRUMC) if MRIU are available for use by the ADS (e.g., CAVH system (e.g.,IRIS of the CAVH system)). If MRIU are available, methods compriseplanning (e.g., by RUMC) a scheduling scheme for the MRIU; and sendingmovement instructions to the MRIU. In some embodiments, methods furthercomprise moving the MRIU to the designated position; and completingautomated driving tasks, e.g., automated driving tasks managed by theIRIS using the MRIU as a temporary RIU. In some embodiments, if MRIU arenot available for use by the ADS (e.g., CAVH system (e.g., IRIS of theCAVH system)), methods comprise reducing the intelligence level of thearea (e.g., locations where the IRIS has no RIU deployed and/or whereMRIU are not available for use by the ADS (e.g., CAVH system (e.g., IRISof the CAVH system))).

In some embodiments, the technology provides a management control methodfor MRIU to supplement coverage of RIU for an IRIS. In some embodiments,the MIRIS is configured to perform a management control method for MRIUto supplement coverage of RIU for an IRIS. In some embodiments, methodscomprise receiving (e.g., by RUMC) a command to detect the deploymentposition of RIU (e.g., collecting deployment data describing thedeployment locations of RIU); and determining (e.g., by RUMC) if MRIUare available for use by the ADS (e.g., CAVH system (e.g., IRIS of theCAVH system)). In some embodiments, methods comprise detecting (e.g., byRUMC) the deployment position of RIU; and determining (e.g., by RUMC) ifMRIU are available for use by the ADS (e.g., CAVH system (e.g., IRIS ofthe CAVH system)). If MRIU are available, methods comprise planning(e.g., by RUMC) a scheduling scheme for the MRIU; and sending movementinstructions to the MRIU. In some embodiments, methods further comprisemoving the MRIU to the designated position; and collecting and uploadingdata describing the deployment of RIU and/or MRIU to the RUMC. In someembodiments, methods comprise determining (e.g., calculating) (e.g., byRUMC) an optimal location of RIU based on the detection results.

Although the disclosure herein refers to certain illustratedembodiments, it is to be understood that these embodiments are presentedby way of example and not by way of limitation.

For example, e.g., as shown in FIG. 1, the MIRIS comprises componentsarranged in an architecture and data flows. In some embodiments, theMIRIS comprises structural components, e.g., a Mobile RoadsideIntelligent Unit (MRIU) 101, a Traffic Operation Center (TOC) 102, aTraffic Control Center (TCC) 103, a Traffic Control Unit (TCU) 104,and/or a Roadside communication system 105.

In some embodiments, e.g., as shown in FIG. 2, the MIRIS interacts withother systems. In particular, in some embodiments, the MRIU 101exchanges data and information with RIU 201, TCU 103, TCC 104, TOC 102,and/or VIU 202.

In some embodiments, e.g., as shown in FIG. 3A, the technology providesa RUMC system (e.g., comprising components arranged in an architectureand data flows). In some embodiments, the RUMC system 301 comprises aninformation transmission subsystem 302, a data management subsystem 303,a mobile service subsystem 304, and/or a security control subsystem 305.The information transmission subsystem 302 provides informationexchange, data transmission 302, and/or control instruction distributionamong the RUMC system 301, MRIU 101, and/or IRIS 310. The datamanagement subsystem 303 stores the number, location, status, energyconsumption, and other parameter information of the MRIUs 101 in theMIRIS. The data management subsystem records the scene data, thereal-time data of MRIU 101, and the historical movement plans of theMRIU 101. Furthermore, the data management provides data backup forlocation adjustment of MRIU 101 in the road network and/or movementplans generated by the mobile service subsystem 304. The mobile servicesubsystem 304 analyzes the mission requirements; and formulates the MRIU101 deployment plan according to the corresponding scene and MRIUparameters recorded in the data management subsystem (e.g., location,status, and energy consumption information). The mobile servicesubsystem 304 provides specific MRIU control strategies and taskinstructions to adjust the location of MRIU. The security controlsubsystem 305 confirms the MRIU movement commands provided by the mobileservice subsystem 304 and sends the MRIU movement commands to theinformation transmission subsystem 302 for execution, which maximizesthe accuracy and control security for the MRIU.

In some embodiments, e.g., as shown in FIG. 3B, the technology providesmethods for the operation of the RUMC system. In some embodiments, theinformation transmission subsystem receives the service request sent bythe IRIS or MRIU. The data management subsystem backs up the servicerequest. The mobile service subsystem analyzes the specific workscenario of the service request. The mobile service subsystem determinesif the MIRIS can provide services in this scenario. If the servicescannot be provided, the mobile service subsystem generates a commandindicating that the MIRIS cannot meet the service requirements andtransmits the command to the information transmission subsystem. Theinformation transmission subsystem sends the command to the IRIS orMRIU. If services can be provided, the mobile service subsystem selectsthe corresponding work modules according to the service requirements ofthe scene and generates the deployment plan and control instructions.The security control subsystem confirms the deployment plan and controlinstructions. The information transmission subsystem sends thedeployment plan and control instructions to the IRIS or MRIU.

In some embodiments, e.g., as shown in FIG. 4, the RUMC comprises amobile service subsystem. As shown in FIG. 4, the mobile servicesubsystem comprises a dynamic deployment module 401, an emergencyservice module 402, and an auxiliary application module 403. The dynamicdeployment module 401 solves the problem of imbalance between serviceand demand caused by CAV flow changes in different time periods and/ordifferent areas. Through the perception and recognition of singlescenario or combined scenarios, the dynamic deployment module 401provides deployment plans to adjust the number and/or position of MRIUsin the road network, thus providing a dynamic balance between servicecapabilities and demands for service resulting from traffic flow. Theemergency service module 402 provides solutions to “long tail”phenomenon existing in autonomous driving. The emergency service module402 can perceive, recognize, and analyze a variety of emergencyscenarios such as severe weather, incidents, construction, specialevents, and social security incidents. The emergency service module 402generates the MRIU management and control strategies in response toemergency scenarios and supplements or enhances the perception,prediction, decision-making, and vehicle control functions of theautonomous driving system in special scenarios. The auxiliaryapplication module 403 provides MRIU control strategies or schemes forother service requirements in the autonomous driving system, such asassisting the installation of fixed RIU in the IRIS, updatinghigh-precision map system, and collecting traffic information.

In some embodiments, e.g., as shown in FIG. 5, the MRIU comprises anumber of modules arranged in an architecture and data flows. Inparticular, the intelligent sensing module 501 detects and monitors theenvironment through radar, camera, lidar, and weather sensors. The GNSSand inertial navigation systems are used to sense the mobile state ofMRIU. The intelligent communication module 504 provides data exchangebetween MRIU 101 and RIU 201, TCU 103, TCC 104, TOC 102, and/or VIU 202with multi-mode communication of LTE-V2X, WiFi, GPS/BeiDou, 4G, 5G, 6G,and/or 7G. The intelligent computing module 502 provides data fusion andfeature extraction for the traffic information collected by theintelligent sensing module 501. The intelligent computing modulecombines the mesoscopic and macroscopic traffic information provided bythe multi-level cloud platform to predict short-term traffic flow stateand optimize the moving speed and path for MRIU in real-time. Theintelligent decision control module 503 uses the data processed by theintelligent computing module 502 to formulate vehicle controlstrategies, generate vehicle control instructions, and distributevehicle control information for the connected automated vehicles. Theintelligent decision control module 503 also determines the moving speedand path of MRIU. The intelligent mobile module 505 moves the MRIUaccording to the pre-determined speed and path. In case of failure ordelay, the intelligent mobile module 505 feeds back the information tothe intelligent decision control module 503 (e.g., in real-time). Theintelligent display module 506 can assist the driving oflow-intelligence-level (e.g., V1, V1.5, V2) connected automated vehiclesand high-intelligent-level (e.g., V3, V4, V5) connected automatedvehicles having a VIU failure according to the control instructionsgenerated by intelligent decision control module 503.

In some embodiments, e.g., as shown in FIG. 6, the intelligent computingmodule comprises components arranged in an architecture and data flows.The data storage unit 601 stores traffic information collected by theintelligent sensing module 501 and the traffic information processed bythe multi-level cloud platform. The edge computing unit 602 performsdata fusion and feature extraction for the traffic information collectedby the intelligent sensing module 501. The edge computing unit combinesthe mesoscopic and macroscopic traffic information 510 provided by themulti-level cloud platform to make a short-term prediction 607 for thetraffic flow parameters of a lane and the movement state of theconnected automated vehicle. According to the information 605 providedby the data storage unit 601 and the prediction 605 provided by edgecomputing unit 602, the route planning unit 603 obtains the optimizationresult 608 of the moving speed and path for MRIU in real-time.

In some embodiments, e.g., as shown in FIG. 7, the intelligent decisioncontrol module comprises components arranged in an architecture and dataflows. The decision-making unit 702 uses the data processed by theintelligent computing module 502 to make traffic management decisions704. The control unit 701 makes control instructions 512 for theconnected automated vehicle with different intelligent levels accordingto the information 704 provided by the decision-making unit 702. Thecontrol instruction 516 is generated to control intelligent displaymodule 506 to enhance safety control of the connected automated vehiclein various special scenarios. The route selection unit 703 determinesthe mobile path 514 according to the deployment task of the RUMC 513 andthe mobile scheme 608 provided by the intelligent computing module 502.The intelligent decision control module 503 judges whether the plannedpath 514 can meet the service task assigned by the RUMC in conjunctionwith the movement status information of the MRIU 515, which is returnedby the intelligent mobile module 505.

In some embodiments, e.g., as shown in FIG. 8, the technology provides amethod for moving MRIU. The intelligent communication module receives adeployment command from the RUMC. The intelligent computing module plansthe moving path and the moving speed by combining the predictioninformation and attribute information of the MRIU. The intelligentdecision control module selects and confirms the moving path and sendsthe information to the intelligent mobile module. The intelligent mobilemodule moves the MRIU according to the preset moving path and movingspeed, and the intelligent mobile module monitors the movement status ofMRIU in real-time. If the intelligent sensing module detects obstaclesin the path of the MRIU or the intelligent mobile module detectsabnormal conditions, the intelligent computing module re-plans the MRIUmoving path based on real-time environment information and parameterinformation of the MRIU. If the intelligent decision control moduledetermines that the MRIU cannot reach the task location on time usingthe new planning path, the intelligent decision control module willupload the task failure information to the RUMC, and the MRIU will waitfor further instructions from the RUMC. Alternatively, if theintelligent decision control module determines that the MRIU can reachthe task location on time using the new planning path, the intelligentmobile module will move the MRIU according to the updated path.

In some embodiments, e.g., as shown in FIG. 9, the technology providesmethods for a management control method for MRIU when the RIUs of theIRIS malfunction, cease to function, or the RIUs are unable to meet therequirements of the automated driving function. When the IRIS detectspartial RIU failure or that an RIU fails to meet the traffic demand, theIRIS makes internal adjustments. If the failure cannot be eliminatedand/or addressed by IRIS, the IRIS sends a service request to the RUMC.Next, the RUMC detects whether there are MRIUs that can be callable inthe system (e.g., provided to the IRIS). If there are MRIUs that can becalled in the system (e.g., provided to the IRIS), the RUMC plans a MRIUscheduling scheme and sends moving instructions and work tasks to theselected MRIUs. Finally, the MRIUs move to the specified location andperform automatic driving tasks in cooperation with the RIU. If thereare no MRIUs that can be called in the system (e.g., provided to IRIS),the intelligence level of this area is reduced.

In some embodiments, e.g., as shown in FIG. 10, the technology providesa management control method for MRIU when the IRIS has no RIUs incertain locations. As shown in FIG. 10, after the IRIS detects servicedemands in an area without RIUs, IRIS sends a service request to theRUMC. The RUMC detects if there are MRIUs available. If there are MRIUsavailable, the RUMC plans the scheduling scheme of the MRIU and sendsmovement instructions and tasks to the MRIU. Then, the MRIU moves to thedesignated position to complete the automatic driving task arranged bythe IRIS (e.g., the MRIU acts as a temporary RIU). If there is no MRIUavailable in the system, the intelligence level of this area is reduced.

In some embodiments, e.g., as shown in FIG. 11, the technology providesa management control method for the MRIU to improve the layout of RIUsfor the IRIS (e.g., to supplement the coverage of a road network by RIUand/or MRIU). As shown in FIG. 11, after the RUMC receives a command todetect the deployment position of RIU, the RUMC will detect whetherthere are MRIUs that can be used to collect the detection performancedata. If there are MRIUs available, the RUMC plans the scheduling schemeof the MRIU and sends movement instructions and tasks to the MRIU. Then,the MRIU moves to the pre-set location for detection and uploads thedetection data to the RUMC. Finally, the RUMC calculates the optimallocation of the RIU.

Automated Driving Systems (ADS)

In some embodiments, the technology provides improvements (e.g., aMIRIS) for a vehicle operations and control system (e.g., an ADS andtechnologies as described herein). In some embodiments, the ADScomprises one or more of a roadside intelligent unit (RIU) network; aTraffic Control Unit (TCU), a Traffic Control Center (TCC); a TCU/TCCnetwork; a vehicle intelligent unit (VIU) (e.g., a vehicle comprising aVIU); and/or a Traffic Operations Center (TOC). In some embodiments, thesystem comprises multiple kinds of sensors and computation devices onCAV and infrastructure (e.g., roadside infrastructure) and is configuredto integrate sensing, prediction, planning, and control for automateddriving of CAV.

In some embodiments, the technology relates to an ADS provided as aconnected and automated vehicle highway (CAVH) system, e.g., comprisingone or more components of an intelligent road infrastructure system(see, e.g., U.S. Pat. Nos. 10,867,512 and 10,380,886, each of which isincorporated herein by reference). In some embodiments, the ADS isprovided as or supports a distributed driving system (DDS), intelligentroadside toolbox (IRT), and/or device allocation system (DAS) (see,e.g., U.S. patent application Ser. Nos. 16/996,684; 63/004,551; and63/004,564, each of which is incorporated herein by reference). In someembodiments, the term “roadside intelligent unit” and its abbreviation“RIU” are used to refer to the components named a “roadside unit” andits abbreviation “RSU”, respectively, as described for the CAVHtechnology in, e.g., U.S. Pat. Nos. 10,867,512 and 10,380,886, each ofwhich is incorporated herein by reference. In some embodiments, the term“vehicle intelligent unit” and its abbreviation “VIU” are used to referto the components named an “onboard unit” and its abbreviation “OBU”,respectively, as described for the CAVH technology in, e.g., U.S. Pat.Nos. 10,867,512 and 10,380,886, each of which is incorporated herein byreference. In some embodiments, the term “vehicle intelligent unit” andits abbreviation “VIU” are used to refer to the components named an“onboard intelligent unit” and its abbreviation “OIU”, respectively, asdescribed in U.S. Pat. App. Ser. No. 63/042,620, incorporated herein byreference.

In some embodiments, the technology provides a system (e.g., a vehicleoperations and control system comprising a RIU and/or an RIU network; aTCU/TCC network; a vehicle comprising an vehicle intelligent unit; aTOC; and/or a cloud-based platform configured to provide information andcomputing services (see, e.g., U.S. patent application Ser. No.16/454,268, incorporated herein by reference)) configured to providesensing functions, transportation behavior prediction and managementfunctions, planning and decision making functions, and/or vehiclecontrol functions. In some embodiments, the system comprises wiredand/or wireless communications media. In some embodiments, the systemcomprises a power supply network. In some embodiments, the systemcomprises a cyber-safety and security system. In some embodiments, thesystem comprises a real-time communication function.

In some embodiments, the RIU network comprises an RIU subsystem. In someembodiments, the RIU network comprises one or more MRIU as describedherein. In some embodiments, the RIU subsystem comprises a sensingmodule configured to measure characteristics of the driving environment;a communication module configured to communicate with vehicles, TCUs,and the cloud; a data processing module configured to process, fuse, andcompute data from the sensing and/or communication modules; an interfacemodule configured to communicate between the data processing module andthe communication module; and an adaptive power supply module configuredto provide power and to adjust power according to the conditions of thelocal power grid. In some embodiments, the adaptive power supply moduleis configured to provide backup redundancy. In some embodiments, thecommunication module communicates using wired or wireless media.

In some embodiments, the sensing module comprises a radar based sensor.In some embodiments, the sensing module comprises a vision based sensor.In some embodiments, the sensing module comprises a radar based sensorand a vision based sensor and wherein the vision based sensor and theradar based sensor are configured to sense the driving environment andvehicle attribute data. In some embodiments, the radar based sensor is aLIDAR, microwave radar, ultrasonic radar, or millimeter radar. In someembodiments, the vision based sensor is a camera, infrared camera, orthermal camera. In some embodiments, the camera is a color camera.

In some embodiments, the sensing module comprises a global navigationsatellite system (GNSS). In some embodiments, the sensing modulecomprises an inertial navigation system. In some embodiments, thesensing module comprises a satellite based navigation system and aninertial navigation system and the sensing module and/or the inertialnavigation system are configured to provide vehicle location data. Insome embodiments, the GNSS is, e.g., the Global Positioning Systemdeveloped by the United States, Differential Global Positioning System(DGPS), BeiDou Navigation Satellite System (BDS) System, GLONASS GlobalNavigation Satellite System), European Union Galileo positioning system,the NavIC system of India, and the Quasi-Zenith Satellite System (QZSS)of Japan.

In some embodiments, the sensing module comprises a vehicleidentification device. In some embodiments, the vehicle identificationdevice comprises RFID, Bluetooth, Wi-fi (IEEE 802.11), or a cellularnetwork radio, e.g., a 4G, 5G, 6G, or 7G cellular network radio.

In some embodiments, the RIU subsystem comprises RIU deployed on amobile component, e.g., to provide a MRIU as described herein. In someembodiments, the RIU subsystem comprises RIU (e.g., MRIU) deployed on awheeled vehicle. In some embodiments, the RIU subsystem comprises RIU(e.g., MRIU) deployed on a vehicle drone over a critical location, on anunmanned aerial vehicle (UAV), at a site of traffic congestion, at asite of a traffic accident, at a site of highway construction, and/or ata site of extreme weather.

In some embodiments, the RIU subsystem comprises a MRIU comprising asensing module configured to measure characteristics of the drivingenvironment; a communication module configured to communicate withvehicles, TCUs, and the cloud; a data processing module configured toprocess, fuse, and compute data from the sensing and/or communicationmodules; an interface module configured to communicate between the dataprocessing module and the communication module; and an adaptive powersupply module configured to provide power and to adjust power accordingto the conditions of the local power grid. In some embodiments, theadaptive power supply module is configured to provide backup redundancy.In some embodiments, the communication module communicates using wiredor wireless media.

In some embodiments, the MRIU comprises a sensing module comprising aradar based sensor. In some embodiments, the sensing module comprises avision based sensor. In some embodiments, the sensing module comprises aradar based sensor and a vision based sensor and wherein the visionbased sensor and the radar based sensor are configured to sense thedriving environment and vehicle attribute data. In some embodiments, theradar based sensor is a LIDAR, microwave radar, ultrasonic radar, ormillimeter radar. In some embodiments, the vision based sensor is acamera, infrared camera, or thermal camera. In some embodiments, thecamera is a color camera.

In some embodiments, the MRIU sensing module comprises a globalnavigation satellite system (GNSS). In some embodiments, the sensingmodule comprises an inertial navigation system. In some embodiments, thesensing module comprises a satellite based navigation system and aninertial navigation system and the sensing module and/or the inertialnavigation system are configured to provide vehicle location data. Insome embodiments, the GNSS is, e.g., the Global Positioning Systemdeveloped by the United States, Differential Global Positioning System(DGPS), BeiDou Navigation Satellite System (BDS) System, GLONASS GlobalNavigation Satellite System), European Union Galileo positioning system,the NavIC system of India, and the Quasi-Zenith Satellite System (QZSS)of Japan.

In some embodiments, the MRIU sensing module comprises a vehicleidentification device. In some embodiments, the vehicle identificationdevice comprises RFID, Bluetooth, Wi-fi (IEEE 802.11), or a cellularnetwork radio, e.g., a 4G, 5G, 6G, or 7G cellular network radio.

In some embodiments, the RIU subsystem comprises RIU deployed at a fixedlocation near a road comprising automated lanes and, optionally,human-driven lanes. In some embodiments, the RIU subsystem comprises RIUdeployed at a fixed location near road infrastructure. In someembodiments, the RIU subsystem comprises RIU deployed near a highwayroadside, a highway onramp, a highway offramp, an interchange,intersection, a bridge, a tunnel, a toll station, or on a drone over acritical location. In some embodiments, an RIU subsystem comprises RIUpositioned according to road geometry, traffic amount, traffic capacity,vehicle type using a road, road size, and/or geography of the area. Insome embodiments, the RIU subsystem comprises RIU installed on a gantry(e.g., an overhead assembly, e.g., on which highway signs or signals aremounted). In some embodiments, the RIU subsystem comprises RIU installedusing a single cantilever or dual cantilever support.

In some embodiments, the TCC network is configured to provide trafficoperation optimization, data processing, and archiving. In someembodiments, the TCC network comprises a human operations interface. Insome embodiments, the TCC network is a macroscopic TCC, a regional TCC,or a corridor TCC based on the geographical area covered by the TCCnetwork. See, e.g., U.S. Pat. Nos. 10,380,886; 10,867,512; 10,692,365;and U.S. Pat. App. Pub. Nos. 20200005633 and 20200021961, each of whichis incorporated herein by reference.

In some embodiments, the TCU network is configured to provide real-timevehicle control and data processing. In some embodiments, the real-timevehicle control and data processing are automated based on preinstalledalgorithms. In some embodiments, the TCU network comprises a segment TCUor a point TCU based on based on the geographical area covered by theTCU network. In some embodiments, the system comprises a point TCUphysically combined or integrated with an RIU. In some embodiments, thesystem comprises a segment TCU physically combined or integrated with aRIU. See, e.g., U.S. Pat. Nos. 10,380,886; 10,867,512; 10,692,365; andU.S. Pat. App. Pub. Nos. 20200005633 and 20200021961, each of which isincorporated herein by reference.

In some embodiments, the TCC network comprises macroscopic TCCsconfigured to process information from regional TCCs and provide controltargets to regional TCCs; regional TCCs configured to processinformation from corridor TCCs and provide control targets to corridorTCCs; and corridor TCCs configured to process information frommacroscopic and segment TCUs and provide control targets to segmentTCUs. See, e.g., U.S. Pat. Nos. 10,380,886; 10,867,512; 10,692,365; andU.S. Pat. App. Pub. Nos. 20200005633 and 20200021961, each of which isincorporated herein by reference.

In some embodiments, the TCU network comprises segment TCUs configuredto process information from corridor and/or point TOCs and providecontrol targets to point TCUs; and point TCUs configured to processinformation from the segment TCU and RIUs and provide vehicle-basedcontrol instructions (e.g., detailed and time-sensitive controlinstructions for individual vehicles) to an RIU. See, e.g., U.S. Pat.Nos. 10,380,886; 10,867,512; 10,692,365; and U.S. Pat. App. Pub. Nos.20200005633 and 20200021961, each of which is incorporated herein byreference.

In some embodiments, the RIU network provides vehicles with customizedtraffic information and control instructions (e.g., detailed andtime-sensitive control instructions for individual vehicles) andreceives information provided by vehicles.

In some embodiments, the TCC network comprises one or more TCCscomprising a connection and data exchange module configured to providedata connection and exchange between TCCs. In some embodiments, theconnection and data exchange module comprises a software componentproviding data rectify, data format convert, firewall, encryption, anddecryption methods. In some embodiments, the TCC network comprises oneor more TCCs comprising a transmission and network module configured toprovide communication methods for data exchange between TCCs. In someembodiments, the transmission and network module comprises a softwarecomponent providing an access function and data conversion betweendifferent transmission networks within the cloud platform. In someembodiments, the TCC network comprises one or more TCCs comprising aservice management module configured to provide data storage, datasearching, data analysis, information security, privacy protection, andnetwork management functions. In some embodiments, the TCC networkcomprises one or more TCCs comprising an application module configuredto provide management and control of the TCC network. In someembodiments, the application module is configured to manage cooperativecontrol of vehicles and roads, system monitoring, emergency services,and human and device interaction.

In some embodiments, TCU network comprises one or more TCUs comprising asensor and control module configured to provide the sensing and controlfunctions of an RIU. In some embodiments, the sensor and control moduleis configured to provide the sensing and control functions of radar,camera, RFID, and/or V2I (vehicle-to-infrastructure) equipment. In someembodiments, the sensor and control module comprises a DSRC, GPS, 4G,5G, 6G, 7G, and/or wireless (e.g., IEEE 802.11) radio. In someembodiments, the TCU network comprises one or more TCUs comprising atransmission and network module configured to provide communicationnetwork function for data exchange between an automated vehicle and aRIU. In some embodiments, the TCU network comprises one or more TCUscomprising a service management module configured to provide datastorage, data searching, data analysis, information security, privacyprotection, and network management. In some embodiments, the TCU networkcomprises one or more TCUs comprising an application module configuredto provide management and control methods of an RIU. In someembodiments, the management and control methods of an RIU comprise localcooperative control of vehicles and roads, system monitoring, andemergency service. In some embodiments, the TCC network comprises one ormore TCCs further comprising an application module and the servicemanagement module provides data analysis for the application module. Insome embodiments, the TCU network comprises one or more TCUs furthercomprising an application module and the service management moduleprovides data analysis for the application module.

In some embodiments, the TOC comprises interactive interfaces. In someembodiments, the interactive interfaces provide control of the TCCnetwork and data exchange. In some embodiments, the interactiveinterfaces comprise information sharing interfaces and vehicle controlinterfaces. In some embodiments, the information sharing interfacescomprise an interface that shares and obtains traffic data; an interfacethat shares and obtains traffic incidents; an interface that shares andobtains passenger demand patterns from shared mobility systems; aninterface that dynamically adjusts prices according to instructionsgiven by the vehicle operations and control system; and/or an interfacethat allows a special agency (e.g., a vehicle administrative office orpolice) to delete, change, and/or share information. In someembodiments, the vehicle control interfaces comprise an interface thatallows a vehicle operations and control system to assume control ofvehicles; an interface that allows vehicles to form a platoon with othervehicles; and/or an interface that allows a special agency (e.g., avehicle administrative office or police) to assume control of a vehicle.In some embodiments, the traffic data comprises vehicle density, vehiclevelocity, and/or vehicle trajectory. In some embodiments, the trafficdata is provided by the vehicle operations and control system and/orother shared mobility systems. In some embodiments, traffic incidentscomprise extreme conditions, major and/or minor accident, and/or anatural disaster. In some embodiments, an interface allows the vehicleoperations and control system to assume control of vehicles uponoccurrence of a traffic event, extreme weather, or pavement breakdownwhen alerted by the vehicle operations and control system and/or othershared mobility systems. In some embodiments, an interface allowsvehicles to form a platoon with other vehicles when they are driving inthe same automated vehicle dedicated lane.

In some embodiments, the VIU comprises a communication module configuredto communicate with an RIU and/or MRIU. In some embodiments, the VIUcomprises a communication module configured to communicate with anotherVIU. In some embodiments, the VIU comprises a data collection moduleconfigured to collect data from external vehicle sensors and internalvehicle sensors; and to monitor vehicle status and driver status. Insome embodiments, the VIU comprises a vehicle control module configuredto execute control instructions for driving tasks. In some embodiments,the driving tasks comprise car following and/or lane changing. In someembodiments, the control instructions are received from an RIU and/orMRIU. In some embodiments, the VIU is configured to control a vehicleusing data received from an RIU and/or MRIU. In some embodiments, thedata received from the RIU comprises vehicle control instructions (e.g.,detailed and time-sensitive control instructions for individualvehicles); travel route and traffic information; and/or servicesinformation. In some embodiments, the vehicle control instructionscomprise a longitudinal acceleration rate, a lateral acceleration rate,and/or a vehicle orientation. In some embodiments, the travel route andtraffic information comprise traffic conditions, incident location,intersection location, entrance location, and/or exit location. In someembodiments, the services data comprises the location of a fuel stationand/or location of a point of interest. In some embodiments, a VIU isconfigured to send data to an RIU and/or MRIU. In some embodiments, thedata sent to the RIU and/or MRIU comprises driver input data; drivercondition data; and/or vehicle condition data. In some embodiments, thedriver input data comprises origin of the trip, destination of the trip,expected travel time, and/or service requests. In some embodiments, thedriver condition data comprises driver behaviors, fatigue level, and/ordriver distractions. In some embodiments, the vehicle condition datacomprises vehicle ID, vehicle type, and/or data collected by a datacollection module.

In some embodiments, the VIU is configured to collect data comprisingvehicle engine status; vehicle speed; surrounding objects detected byvehicles; and/or driver conditions. In some embodiments, the VIU isconfigured to assume control of a vehicle. In some embodiments, the VIUis configured to assume control of a vehicle when the automated drivingsystem fails. In some embodiments, the VIU is configured to assumecontrol of a vehicle when the vehicle condition and/or traffic conditionprevents the automated driving system from driving the vehicle. In someembodiments, the vehicle condition and/or traffic condition is adverseweather conditions, a traffic incident, a system failure, and/or acommunication failure.

All publications and patents mentioned in the above specification areherein incorporated by reference in their entirety for all purposes.Various modifications and variations of the described compositions,methods, and uses of the technology will be apparent to those skilled inthe art without departing from the scope and spirit of the technology asdescribed. Although the technology has been described in connection withspecific exemplary embodiments, it should be understood that theinvention as claimed should not be unduly limited to such specificembodiments. Indeed, various modifications of the described modes forcarrying out the invention that are obvious to those skilled in the artare intended to be within the scope of the following claims.

1. A Mobile Intelligent Road Infrastructure System (MIRIS) comprisingthe following physical subsystems: a Mobile Roadside Intelligent Unit(MRIU); and a Roadside Unit Management Control (RUMC) system configuredto identify optimal MRIU deployment locations and deploy MRIU to saiddeployment locations. 2-4. (canceled)
 5. The MIRIS of claim 1 configuredto support an ADS by providing one or more mobile roadside intelligentunits (MRIU) to said ADS.
 6. The MIRIS of claim 1, wherein said MIRIS issupported by a multi-level cloud platform.
 7. (canceled)
 8. The MIRIS ofclaim 5, wherein said ADS is a road-based ADS, a connected and automatedvehicle (CAV)-based ADS, a cloud-based ADS, and/or a high precisionmap-based ADS.
 9. The MIRIS of claim 1 configured to serve automatedvehicles (AV) and/or connected and automated vehicles (CAV) having anintelligence level of V1, V1.5, V2, V3, V4, and/or V5.
 10. The MIRIS ofclaim 1 configured to receive data from a Vehicle Intelligent Unit (VIU)and/or an MRIU, generate vehicle control instructions, and/or sendvehicle control instructions to a VIU.
 11. The MIRIS of claim 1configured to complement, enhance, back-up, elevate, provide, and/orreplace automated driving functions provided by an ADS, wherein saidautomated driving functions are sensing, prediction, decision-making,and vehicle control. 12-29. (canceled)
 30. The MIRIS of claim 1, whereinsaid TOC is configured to provide vehicle control and traffic managementstrategies, adjust a position of an MRIU, and/or provide automateddriving functions through said RUMC system. 31-43. (canceled)
 44. TheMIRIS of claim 1, wherein said RUMC system comprises an informationtransmission subsystem, a data management subsystem, a mobile servicesubsystem, and/or a security control subsystem. 45-52. (canceled) 53.The MIRIS of claim 1, wherein said RUMC system is configured to: a)receive, by the information transmission subsystem, a service requestsent by the IRIS or the MRIU; b) back up, by the data managementsubsystem, the service request; c) analyze, by the mobile servicesubsystem, the specific working scenario of the service request; d)determine, by the mobile service subsystem, if the MIRIS can provideservices in the specific working scenario; and e) perform either (i) or(ii): i) if the MIRIS cannot provide services in the specific workingscenario: generate, by the mobile service subsystem, a command that theMIRIS cannot meet the service requirements; transmit the command to theinformation transmission subsystem; and send, by the informationtransmission subsystem, the command to IRIS and/or MRIU indicating thatMIRIS cannot meet the service requirements; or ii) if the MIRIS canprovide services in the specific working scenario: select, by the mobileservice subsystem, work modules according to the specific servicerequirements; generate a layout scheme and MRIU control instructions;confirm, by the safety control subsystem, the layout scheme and MRIUcontrol instructions; and send, by the information transmissionsubsystem, the layout scheme and MRIU control instructions to IRISand/or MRIU.
 54. The MIRIS of claim 44, wherein the mobile servicesubsystem comprises a dynamic deployment module configured to adjust thelocation of MRIU to balance the ADS services and demands for ADSservices. 55-59. (canceled)
 60. The MIRIS of claim 1, wherein said MRIUcomprises an intelligent sensing module; an intelligent communicationmodule; an intelligent computing module; an intelligent decision controlmodule; an intelligent mobile module; and/or an intelligent displaymodule. 61-107. (canceled)
 108. The MIRIS of claim 1, wherein the MRIUis configured to a) receive, by the intelligent communication module, adeployment command from the RUMC; b) plan, by the intelligent computingmodule, a moving path and/or a moving speed for MRIU; c) select, by theintelligent decision control module, a moving path and/or moving speedand sending the moving path and/or moving speed information to theintelligent mobile module; d) move, by the intelligent mobile module,the MRIU according to the moving path and/or moving speed; and e) move,by the intelligent mobile module, the movement status of the MRIU.109-182. (canceled)
 183. The MIRIS of claim 1, further comprising one ormore of the following physical subsystems: a Traffic Operation Center(TOC); a Traffic Control Center (TCC) and Traffic Control Unit (TCU);and/or a roadside communication system.